| 2022 | "Lossless" Compression of Deep Neural Networks: A High-dimensional Neural Tangent Kernel Approach. Lingyu Gu, Yongqi Du, Yuan Zhang, Di Xie, Shiliang Pu, Robert C. Qiu, Zhenyu Liao |
| 2022 | "Why Not Other Classes?": Towards Class-Contrastive Back-Propagation Explanations. Yipei Wang, Xiaoqian Wang |
| 2022 | $\alpha$-ReQ : Assessing Representation Quality in Self-Supervised Learning by measuring eigenspectrum decay. Kumar Krishna Agrawal, Arnab Kumar Mondal, Arna Ghosh, Blake A. Richards |
| 2022 | $k$-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension. Ziv Goldfeld, Kristjan H. Greenewald, Theshani Nuradha, Galen Reeves |
| 2022 | (De-)Randomized Smoothing for Decision Stump Ensembles. Miklós Z. Horváth, Mark Niklas Müller, Marc Fischer, Martin T. Vechev |
| 2022 | (Optimal) Online Bipartite Matching with Degree Information. Anders Aamand, Justin Y. Chen, Piotr Indyk |
| 2022 | 360-MLC: Multi-view Layout Consistency for Self-training and Hyper-parameter Tuning. Bolivar Solarte, Chin-Hsuan Wu, Yueh-Cheng Liu, Yi-Hsuan Tsai, Min Sun |
| 2022 | 3D Concept Grounding on Neural Fields. Yining Hong, Yilun Du, Chunru Lin, Josh Tenenbaum, Chuang Gan |
| 2022 | 3DB: A Framework for Debugging Computer Vision Models. Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Yuanqing Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry |
| 2022 | 3DILG: Irregular Latent Grids for 3D Generative Modeling. Biao Zhang, Matthias Nießner, Peter Wonka |
| 2022 | 3DOS: Towards 3D Open Set Learning - Benchmarking and Understanding Semantic Novelty Detection on Point Clouds. Antonio Alliegro, Francesco Cappio Borlino, Tatiana Tommasi |
| 2022 | 4D Unsupervised Object Discovery. Yuqi Wang, Yuntao Chen, Zhaoxiang Zhang |
| 2022 | A Benchmark for Compositional Visual Reasoning. Aimen Zerroug, Mohit Vaishnav, Julien Colin, Sebastian Musslick, Thomas Serre |
| 2022 | A Best-of-Both-Worlds Algorithm for Bandits with Delayed Feedback. Saeed Masoudian, Julian Zimmert, Yevgeny Seldin |
| 2022 | A Boosting Approach to Reinforcement Learning. Nataly Brukhim, Elad Hazan, Karan Singh |
| 2022 | A Causal Analysis of Harm. Sander Beckers, Hana Chockler, Joseph Y. Halpern |
| 2022 | A Character-Level Length-Control Algorithm for Non-Autoregressive Sentence Summarization. Puyuan Liu, Xiang Zhang, Lili Mou |
| 2022 | A Characterization of Semi-Supervised Adversarially Robust PAC Learnability. Idan Attias, Steve Hanneke, Yishay Mansour |
| 2022 | A Classification of $G$-invariant Shallow Neural Networks. Devanshu Agrawal, James Ostrowski |
| 2022 | A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases. James Harrison, Luke Metz, Jascha Sohl-Dickstein |
| 2022 | A Closer Look at Offline RL Agents. Yuwei Fu, Di Wu, Benoit Boulet |
| 2022 | A Closer Look at Prototype Classifier for Few-shot Image Classification. Mingcheng Hou, Issei Sato |
| 2022 | A Closer Look at Weakly-Supervised Audio-Visual Source Localization. Shentong Mo, Pedro Morgado |
| 2022 | A Closer Look at the Adversarial Robustness of Deep Equilibrium Models. Zonghan Yang, Tianyu Pang, Yang Liu |
| 2022 | A Combinatorial Perspective on the Optimization of Shallow ReLU Networks. Michael Matena, Colin Raffel |
| 2022 | A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks. Mingrui Liu, Zhenxun Zhuang, Yunwen Lei, Chunyang Liao |
| 2022 | A Communication-efficient Algorithm with Linear Convergence for Federated Minimax Learning. Zhenyu Sun, Ermin Wei |
| 2022 | A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking. Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang |
| 2022 | A Conditional Randomization Test for Sparse Logistic Regression in High-Dimension. Binh T. Nguyen, Bertrand Thirion, Sylvain Arlot |
| 2022 | A Consistent and Differentiable Lp Canonical Calibration Error Estimator. Teodora Popordanoska, Raphael Sayer, Matthew B. Blaschko |
| 2022 | A Consolidated Cross-Validation Algorithm for Support Vector Machines via Data Reduction. Boxiang Wang, Archer Y. Yang |
| 2022 | A Continuous Time Framework for Discrete Denoising Models. Andrew Campbell, Joe Benton, Valentin De Bortoli, Thomas Rainforth, George Deligiannidis, Arnaud Doucet |
| 2022 | A Contrastive Framework for Neural Text Generation. Yixuan Su, Tian Lan, Yan Wang, Dani Yogatama, Lingpeng Kong, Nigel Collier |
| 2022 | A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated Learning. Zhaomin Wu, Qinbin Li, Bingsheng He |
| 2022 | A Damped Newton Method Achieves Global $\mathcal O \left(\frac{1}{k^2}\right)$ and Local Quadratic Convergence Rate. Slavomír Hanzely, Dmitry Kamzolov, Dmitry Pasechnyuk, Alexander V. Gasnikov, Peter Richtárik, Martin Takác |
| 2022 | A Data-Augmentation Is Worth A Thousand Samples: Analytical Moments And Sampling-Free Training. Randall Balestriero, Ishan Misra, Yann LeCun |
| 2022 | A Dataset for Efforts Towards Achieving the Sustainable Development Goal of Safe Working Environments. Eirik Lund Flogard, Ole Jakob Mengshoel |
| 2022 | A Deep Learning Dataloader with Shared Data Preparation. Jian Xie, Jingwei Xu, Guochang Wang, Yuan Yao, Zenan Li, Chun Cao, Hanghang Tong |
| 2022 | A Deep Reinforcement Learning Framework for Column Generation. Cheng Chi, Amine Mohamed Aboussalah, Elias B. Khalil, Juyoung Wang, Zoha Sherkat-Masoumi |
| 2022 | A Differentiable Semantic Metric Approximation in Probabilistic Embedding for Cross-Modal Retrieval. Hao Li, Jingkuan Song, Lianli Gao, Pengpeng Zeng, Haonan Zhang, Gongfu Li |
| 2022 | A Differentially Private Linear-Time fPTAS for the Minimum Enclosing Ball Problem. Bar Mahpud, Or Sheffet |
| 2022 | A Direct Approximation of AIXI Using Logical State Abstractions. Samuel Yang-Zhao, Tianyu Wang, Kee Siong Ng |
| 2022 | A Fast Post-Training Pruning Framework for Transformers. Woosuk Kwon, Sehoon Kim, Michael W. Mahoney, Joseph Hassoun, Kurt Keutzer, Amir Gholami |
| 2022 | A Fast Scale-Invariant Algorithm for Non-negative Least Squares with Non-negative Data. Jelena Diakonikolas, Chenghui Li, Swati Padmanabhan, Chaobing Song |
| 2022 | A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation. Philip Amortila, Nan Jiang, Dhruv Madeka, Dean P. Foster |
| 2022 | A Fourier Approach to Mixture Learning. Mingda Qiao, Guru Guruganesh, Ankit Singh Rawat, Kumar Avinava Dubey, Manzil Zaheer |
| 2022 | A General Framework for Auditing Differentially Private Machine Learning. Fred Lu, Joseph Munoz, Maya Fuchs, Tyler LeBlond, Elliott Zaresky-Williams, Edward Raff, Francis Ferraro, Brian Testa |
| 2022 | A Geometric Perspective on Variational Autoencoders. Clément Chadebec, Stéphanie Allassonnière |
| 2022 | A Greek Parliament Proceedings Dataset for Computational Linguistics and Political Analysis. Konstantina Dritsa, Aikaterini Thoma, Ioannis Pavlopoulos, Panos Louridas |
| 2022 | A Kernelised Stein Statistic for Assessing Implicit Generative Models. Wenkai Xu, Gesine D. Reinert |
| 2022 | A Lagrangian Duality Approach to Active Learning. Juan Elenter, Navid Naderializadeh, Alejandro Ribeiro |
| 2022 | A Large Scale Search Dataset for Unbiased Learning to Rank. Lixin Zou, Haitao Mao, Xiaokai Chu, Jiliang Tang, Wenwen Ye, Shuaiqiang Wang, Dawei Yin |
| 2022 | A Lower Bound of Hash Codes' Performance. Xiaosu Zhu, Jingkuan Song, Yu Lei, Lianli Gao, Hengtao Shen |
| 2022 | A Mean-Field Game Approach to Cloud Resource Management with Function Approximation. Weichao Mao, Haoran Qiu, Chen Wang, Hubertus Franke, Zbigniew Kalbarczyk, Ravishankar K. Iyer, Tamer Basar |
| 2022 | A Mixture Of Surprises for Unsupervised Reinforcement Learning. Andrew Zhao, Matthieu Gaetan Lin, Yangguang Li, Yong-Jin Liu, Gao Huang |
| 2022 | A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs. Fabian Falck, Christopher Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris C. Holmes, Arnaud Doucet, Matthew Willetts |
| 2022 | A Multi-Task Benchmark for Korean Legal Language Understanding and Judgement Prediction. Wonseok Hwang, Dongjun Lee, Kyoungyeon Cho, Hanuhl Lee, Minjoon Seo |
| 2022 | A Multilabel Classification Framework for Approximate Nearest Neighbor Search. Ville Hyvönen, Elias Jääsaari, Teemu Roos |
| 2022 | A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs. Chloé Rouyer, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin |
| 2022 | A Near-Optimal Primal-Dual Method for Off-Policy Learning in CMDP. Fan Chen, Junyu Zhang, Zaiwen Wen |
| 2022 | A Neural Corpus Indexer for Document Retrieval. Yujing Wang, Yingyan Hou, Haonan Wang, Ziming Miao, Shibin Wu, Qi Chen, Yuqing Xia, Chengmin Chi, Guoshuai Zhao, Zheng Liu, Xing Xie, Hao Sun, Weiwei Deng, Qi Zhang, Mao Yang |
| 2022 | A Neural Pre-Conditioning Active Learning Algorithm to Reduce Label Complexity. Seo Taek Kong, Soomin Jeon, Dongbin Na, Jaewon Lee, Hong-Seok Lee, Kyu-Hwan Jung |
| 2022 | A New Family of Generalization Bounds Using Samplewise Evaluated CMI. Fredrik Hellström, Giuseppe Durisi |
| 2022 | A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models. Lijia Zhou, Frederic Koehler, Pragya Sur, Danica J. Sutherland, Nati Srebro |
| 2022 | A Non-asymptotic Analysis of Non-parametric Temporal-Difference Learning. Eloïse Berthier, Ziad Kobeissi, Francis R. Bach |
| 2022 | A PAC-Bayesian Generalization Bound for Equivariant Networks. Arash Behboodi, Gabriele Cesa, Taco S. Cohen |
| 2022 | A Policy-Guided Imitation Approach for Offline Reinforcement Learning. Haoran Xu, Li Jiang, Jianxiong Li, Xianyuan Zhan |
| 2022 | A Practical, Progressively-Expressive GNN. Lingxiao Zhao, Neil Shah, Leman Akoglu |
| 2022 | A Probabilistic Graph Coupling View of Dimension Reduction. Hugues Van Assel, Thibault Espinasse, Julien Chiquet, Franck Picard |
| 2022 | A Projection-free Algorithm for Constrained Stochastic Multi-level Composition Optimization. Tesi Xiao, Krishnakumar Balasubramanian, Saeed Ghadimi |
| 2022 | A Quadrature Rule combining Control Variates and Adaptive Importance Sampling. Rémi Leluc, François Portier, Johan Segers, Aigerim Zhuman |
| 2022 | A Quantitative Geometric Approach to Neural-Network Smoothness. Zi Wang, Gautam Prakriya, Somesh Jha |
| 2022 | A Reduction to Binary Approach for Debiasing Multiclass Datasets. Ibrahim M. Alabdulmohsin, Jessica Schrouff, Sanmi Koyejo |
| 2022 | A Regret-Variance Trade-Off in Online Learning. Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi |
| 2022 | A Reparametrization-Invariant Sharpness Measure Based on Information Geometry. Cheongjae Jang, Sungyoon Lee, Frank C. Park, Yung-Kyun Noh |
| 2022 | A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits. Ilija Bogunovic, Zihan Li, Andreas Krause, Jonathan Scarlett |
| 2022 | A Rotated Hyperbolic Wrapped Normal Distribution for Hierarchical Representation Learning. Seunghyuk Cho, Juyong Lee, Jaesik Park, Dongwoo Kim |
| 2022 | A Scalable Deterministic Global Optimization Algorithm for Training Optimal Decision Tree. Kaixun Hua, Jiayang Ren, Yankai Cao |
| 2022 | A Simple Approach to Automated Spectral Clustering. Jicong Fan, Yiheng Tu, Zhao Zhang, Mingbo Zhao, Haijun Zhang |
| 2022 | A Simple Decentralized Cross-Entropy Method. Zichen Zhang, Jun Jin, Martin Jägersand, Jun Luo, Dale Schuurmans |
| 2022 | A Simple and Optimal Policy Design for Online Learning with Safety against Heavy-tailed Risk. David Simchi-Levi, Zeyu Zheng, Feng Zhu |
| 2022 | A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits. Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu |
| 2022 | A Single-timescale Analysis for Stochastic Approximation with Multiple Coupled Sequences. Han Shen, Tianyi Chen |
| 2022 | A Solver-free Framework for Scalable Learning in Neural ILP Architectures. Yatin Nandwani, Rishabh Ranjan, Mausam, Parag Singla |
| 2022 | A Spectral Approach to Item Response Theory. Duc Nguyen, Anderson Ye Zhang |
| 2022 | A Statistical Online Inference Approach in Averaged Stochastic Approximation. Chuhan Xie, Zhihua Zhang |
| 2022 | A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization. Songtao Lu, Siliang Zeng, Xiaodong Cui, Mark S. Squillante, Lior Horesh, Brian Kingsbury, Jia Liu, Mingyi Hong |
| 2022 | A Survey and Datasheet Repository of Publicly Available US Criminal Justice Datasets. Miri Zilka, Bradley Butcher, Adrian Weller |
| 2022 | A Theoretical Framework for Inference Learning. Nick Alonso, Beren Millidge, Jeffrey L. Krichmar, Emre O. Neftci |
| 2022 | A Theoretical Study on Solving Continual Learning. Gyuhak Kim, Changnan Xiao, Tatsuya Konishi, Zixuan Ke, Bing Liu |
| 2022 | A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning. Bo Liu, Xidong Feng, Jie Ren, Luo Mai, Rui Zhu, Haifeng Zhang, Jun Wang, Yaodong Yang |
| 2022 | A Theoretical View on Sparsely Activated Networks. Cenk Baykal, Nishanth Dikkala, Rina Panigrahy, Cyrus Rashtchian, Xin Wang |
| 2022 | A Theory of PAC Learnability under Transformation Invariances. Han Shao, Omar Montasser, Avrim Blum |
| 2022 | A Transformer-Based Object Detector with Coarse-Fine Crossing Representations. Zhishan Li, Ying Nie, Kai Han, Jianyuan Guo, Lei Xie, Yunhe Wang |
| 2022 | A Unified Analysis of Federated Learning with Arbitrary Client Participation. Shiqiang Wang, Mingyue Ji |
| 2022 | A Unified Analysis of Mixed Sample Data Augmentation: A Loss Function Perspective. Chanwoo Park, Sangdoo Yun, Sanghyuk Chun |
| 2022 | A Unified Convergence Theorem for Stochastic Optimization Methods. Xiao Li, Andre Milzarek |
| 2022 | A Unified Diversity Measure for Multiagent Reinforcement Learning. Zongkai Liu, Chao Yu, Yaodong Yang, Peng Sun, Zifan Wu, Yuan Li |
| 2022 | A Unified Evaluation of Textual Backdoor Learning: Frameworks and Benchmarks. Ganqu Cui, Lifan Yuan, Bingxiang He, Yangyi Chen, Zhiyuan Liu, Maosong Sun |
| 2022 | A Unified Framework for Alternating Offline Model Training and Policy Learning. Shentao Yang, Shujian Zhang, Yihao Feng, Mingyuan Zhou |
| 2022 | A Unified Framework for Deep Symbolic Regression. Mikel Landajuela, Chak Shing Lee, Jiachen Yang, Ruben Glatt, Cláudio P. Santiago, Ignacio Aravena, Terrell Nathan Mundhenk, Garrett Mulcahy, Brenden K. Petersen |
| 2022 | A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs. Songming Liu, Zhongkai Hao, Chengyang Ying, Hang Su, Jun Zhu, Ze Cheng |
| 2022 | A Unified Model for Multi-class Anomaly Detection. Zhiyuan You, Lei Cui, Yujun Shen, Kai Yang, Xin Lu, Yu Zheng, Xinyi Le |
| 2022 | A Unified Sequence Interface for Vision Tasks. Ting Chen, Saurabh Saxena, Lala Li, Tsung-Yi Lin, David J. Fleet, Geoffrey E. Hinton |
| 2022 | A Unifying Framework for Online Optimization with Long-Term Constraints. Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Giulia Romano, Nicola Gatti |
| 2022 | A Unifying Framework of Off-Policy General Value Function Evaluation. Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang |
| 2022 | A Universal Error Measure for Input Predictions Applied to Online Graph Problems. Giulia Bernardini, Alexander Lindermayr, Alberto Marchetti-Spaccamela, Nicole Megow, Leen Stougie, Michelle Sweering |
| 2022 | A Variant of Anderson Mixing with Minimal Memory Size. Fuchao Wei, Chenglong Bao, Yang Liu, Guangwen Yang |
| 2022 | A Variational Edge Partition Model for Supervised Graph Representation Learning. Yilin He, Chaojie Wang, Hao Zhang, Bo Chen, Mingyuan Zhou |
| 2022 | A Win-win Deal: Towards Sparse and Robust Pre-trained Language Models. Yuanxin Liu, Fandong Meng, Zheng Lin, Jiangnan Li, Peng Fu, Yanan Cao, Weiping Wang, Jie Zhou |
| 2022 | A composable machine-learning approach for steady-state simulations on high-resolution grids. Rishikesh Ranade, Chris Hill, Lalit Ghule, Jay Pathak |
| 2022 | A consistently adaptive trust-region method. Fadi Hamad, Oliver Hinder |
| 2022 | A contrastive rule for meta-learning. Nicolas Zucchet, Simon Schug, Johannes von Oswald, Dominic Zhao, João Sacramento |
| 2022 | A framework for bilevel optimization that enables stochastic and global variance reduction algorithms. Mathieu Dagréou, Pierre Ablin, Samuel Vaiter, Thomas Moreau |
| 2022 | A general approximation lower bound in $L^p$ norm, with applications to feed-forward neural networks. El Mehdi Achour, Armand Foucault, Sébastien Gerchinovitz, François Malgouyres |
| 2022 | A gradient estimator via L1-randomization for online zero-order optimization with two point feedback. Arya Akhavan, Evgenii Chzhen, Massimiliano Pontil, Alexandre B. Tsybakov |
| 2022 | A gradient sampling method with complexity guarantees for Lipschitz functions in high and low dimensions. Damek Davis, Dmitriy Drusvyatskiy, Yin Tat Lee, Swati Padmanabhan, Guanghao Ye |
| 2022 | A new dataset for multilingual keyphrase generation. Frédéric Piedboeuf, Philippe Langlais |
| 2022 | A permutation-free kernel two-sample test. Shubhanshu Shekhar, Ilmun Kim, Aaditya Ramdas |
| 2022 | A sharp NMF result with applications in network modeling. Jiashun Jin |
| 2022 | A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal. Yaqian Zhang, Bernhard Pfahringer, Eibe Frank, Albert Bifet, Nick Jin Sean Lim, Yunzhe Jia |
| 2022 | A theory of weight distribution-constrained learning. Weishun Zhong, Ben Sorscher, Daniel Lee, Haim Sompolinsky |
| 2022 | A time-resolved theory of information encoding in recurrent neural networks. Rainer Engelken, Sven Goedeke |
| 2022 | A2: Efficient Automated Attacker for Boosting Adversarial Training. Zhuoer Xu, Guanghui Zhu, Changhua Meng, Shiwen Cui, Zhenzhe Ying, Weiqiang Wang, Ming Gu, Yihua Huang |
| 2022 | ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection. Huiping Zhuang, Zhenyu Weng, Hongxin Wei, Renchunzi Xie, Kar-Ann Toh, Zhiping Lin |
| 2022 | AD-DROP: Attribution-Driven Dropout for Robust Language Model Fine-Tuning. Tao Yang, Jinghao Deng, Xiaojun Quan, Qifan Wang, Shaoliang Nie |
| 2022 | ADBench: Anomaly Detection Benchmark. Songqiao Han, Xiyang Hu, Hailiang Huang, Minqi Jiang, Yue Zhao |
| 2022 | ALIFE: Adaptive Logit Regularizer and Feature Replay for Incremental Semantic Segmentation. Youngmin Oh, Donghyeon Baek, Bumsub Ham |
| 2022 | ALMA: Hierarchical Learning for Composite Multi-Agent Tasks. Shariq Iqbal, Robby Costales, Fei Sha |
| 2022 | AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation. Yuanfeng Ji, Haotian Bai, Chongjian Ge, Jie Yang, Ye Zhu, Ruimao Zhang, Zhen Li, Lingyan Zhang, Wanling Ma, Xiang Wan, Ping Luo |
| 2022 | AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness. Dacheng Li, Hongyi Wang, Eric P. Xing, Hao Zhang |
| 2022 | APG: Adaptive Parameter Generation Network for Click-Through Rate Prediction. Bencheng Yan, Pengjie Wang, Kai Zhang, Feng Li, Hongbo Deng, Jian Xu, Bo Zheng |
| 2022 | APT-36K: A Large-scale Benchmark for Animal Pose Estimation and Tracking. Yuxiang Yang, Junjie Yang, Yufei Xu, Jing Zhang, Long Lan, Dacheng Tao |
| 2022 | ASPiRe: Adaptive Skill Priors for Reinforcement Learning. Mengda Xu, Manuela Veloso, Shuran Song |
| 2022 | ATD: Augmenting CP Tensor Decomposition by Self Supervision. Chaoqi Yang, Cheng Qian, Navjot Singh, Cao (Danica) Xiao, M. Brandon Westover, Edgar Solomonik, Jimeng Sun |
| 2022 | AUTOMATA: Gradient Based Data Subset Selection for Compute-Efficient Hyper-parameter Tuning. Krishnateja Killamsetty, Guttu Sai Abhishek, Aakriti, Ganesh Ramakrishnan, Alexandre V. Evfimievski, Lucian Popa, Rishabh K. Iyer |
| 2022 | AVLEN: Audio-Visual-Language Embodied Navigation in 3D Environments. Sudipta Paul, Amit Roy-Chowdhury, Anoop Cherian |
| 2022 | AZ-whiteness test: a test for signal uncorrelation on spatio-temporal graphs. Daniele Zambon, Cesare Alippi |
| 2022 | Accelerated Linearized Laplace Approximation for Bayesian Deep Learning. Zhijie Deng, Feng Zhou, Jun Zhu |
| 2022 | Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling. Dmitry Kovalev, Alexander V. Gasnikov, Peter Richtárik |
| 2022 | Accelerated Projected Gradient Algorithms for Sparsity Constrained Optimization Problems. Jan Harold Alcantara, Ching-pei Lee |
| 2022 | Accelerated Training of Physics-Informed Neural Networks (PINNs) using Meshless Discretizations. Ramansh Sharma, Varun Shankar |
| 2022 | Accelerating Certified Robustness Training via Knowledge Transfer. Pratik Vaishnavi, Kevin Eykholt, Amir Rahmati |
| 2022 | Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion. Jialun Zhang, Hong-Ming Chiu, Richard Y. Zhang |
| 2022 | Accelerating Sparse Convolution with Column Vector-Wise Sparsity. Yijun Tan, Kai Han, Kang Zhao, Xianzhi Yu, Zidong Du, Yunji Chen, Yunhe Wang, Jun Yao |
| 2022 | Acceleration in Distributed Sparse Regression. Marie Maros, Gesualdo Scutari |
| 2022 | Action-modulated midbrain dopamine activity arises from distributed control policies. Jack Lindsey, Ashok Litwin-Kumar |
| 2022 | ActionSense: A Multimodal Dataset and Recording Framework for Human Activities Using Wearable Sensors in a Kitchen Environment. Joseph DelPreto, Chao Liu, Yiyue Luo, Michael Foshey, Yunzhu Li, Antonio Torralba, Wojciech Matusik, Daniela Rus |
| 2022 | Active Bayesian Causal Inference. Christian Toth, Lars Lorch, Christian Knoll, Andreas Krause, Franz Pernkopf, Robert Peharz, Julius von Kügelgen |
| 2022 | Active Exploration for Inverse Reinforcement Learning. David Lindner, Andreas Krause, Giorgia Ramponi |
| 2022 | Active Labeling: Streaming Stochastic Gradients. Vivien Cabannes, Francis R. Bach, Vianney Perchet, Alessandro Rudi |
| 2022 | Active Learning Helps Pretrained Models Learn the Intended Task. Alex Tamkin, Dat Nguyen, Salil Deshpande, Jesse Mu, Noah D. Goodman |
| 2022 | Active Learning Polynomial Threshold Functions. Omri Ben-Eliezer, Max Hopkins, Chutong Yang, Hantao Yu |
| 2022 | Active Learning Through a Covering Lens. Ofer Yehuda, Avihu Dekel, Guy Hacohen, Daphna Weinshall |
| 2022 | Active Learning for Multiple Target Models. Ying-Peng Tang, Sheng-Jun Huang |
| 2022 | Active Learning of Classifiers with Label and Seed Queries. Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice, Maximilian Thiessen |
| 2022 | Active Learning with Neural Networks: Insights from Nonparametric Statistics. Yinglun Zhu, Robert Nowak |
| 2022 | Active Learning with Safety Constraints. Romain Camilleri, Andrew Wagenmaker, Jamie H. Morgenstern, Lalit Jain, Kevin Jamieson |
| 2022 | Active Ranking without Strong Stochastic Transitivity. Hao Lou, Tao Jin, Yue Wu, Pan Xu, Quanquan Gu, Farzad Farnoud |
| 2022 | Active Surrogate Estimators: An Active Learning Approach to Label-Efficient Model Evaluation. Jannik Kossen, Sebastian Farquhar, Yarin Gal, Thomas Rainforth |
| 2022 | Active-Passive SimStereo - Benchmarking the Cross-Generalization Capabilities of Deep Learning-based Stereo Methods. Laurent Valentin Jospin, Allen Antony, Lian Xu, Hamid Laga, Farid Boussaïd, Mohammed Bennamoun |
| 2022 | AdaFocal: Calibration-aware Adaptive Focal Loss. Arindam Ghosh, Thomas Schaaf, Matthew Gormley |
| 2022 | Adam Can Converge Without Any Modification On Update Rules. Yushun Zhang, Congliang Chen, Naichen Shi, Ruoyu Sun, Zhi-Quan Luo |
| 2022 | AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition. Shoufa Chen, Chongjian Ge, Zhan Tong, Jiangliu Wang, Yibing Song, Jue Wang, Ping Luo |
| 2022 | Adaptation Accelerating Sampling-based Bayesian Inference in Attractor Neural Networks. Xingsi Dong, Zilong Ji, Tianhao Chu, Tiejun Huang, Wenhao Zhang, Si Wu |
| 2022 | Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking Consistency. Viraj Prabhu, Sriram Yenamandra, Aaditya Singh, Judy Hoffman |
| 2022 | Adapting to Online Label Shift with Provable Guarantees. Yong Bai, Yu-Jie Zhang, Peng Zhao, Masashi Sugiyama, Zhi-Hua Zhou |
| 2022 | Adaptive Data Debiasing through Bounded Exploration. Yifan Yang, Yang Liu, Parinaz Naghizadeh |
| 2022 | Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport. Dandan Guo, Long Tian, He Zhao, Mingyuan Zhou, Hongyuan Zha |
| 2022 | Adaptive Interest for Emphatic Reinforcement Learning. Martin Klissarov, Rasool Fakoor, Jonas W. Mueller, Kavosh Asadi, Taesup Kim, Alexander J. Smola |
| 2022 | Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model. Zhisheng Xiao, Tian Han |
| 2022 | Adaptive Oracle-Efficient Online Learning. Guanghui Wang, Zihao Hu, Vidya Muthukumar, Jacob D. Abernethy |
| 2022 | Adaptive Sampling for Discovery. Ziping Xu, Eunjae Shim, Ambuj Tewari, Paul M. Zimmerman |
| 2022 | Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization. Ali Kavis, Stratis Skoulakis, Kimon Antonakopoulos, Leello Tadesse Dadi, Volkan Cevher |
| 2022 | Adaptively Exploiting d-Separators with Causal Bandits. Blair L. Bilodeau, Linbo Wang, Daniel M. Roy |
| 2022 | Additive MIL: Intrinsically Interpretable Multiple Instance Learning for Pathology. Syed Ashar Javed, Dinkar Juyal, Harshith Padigela, Amaro Taylor-Weiner, Limin Yu, Aaditya Prakash |
| 2022 | Addressing Leakage in Concept Bottleneck Models. Marton Havasi, Sonali Parbhoo, Finale Doshi-Velez |
| 2022 | Addressing Resource Scarcity across Sign Languages with Multilingual Pretraining and Unified-Vocabulary Datasets. Gokul NC, Manideep Ladi, Sumit Negi, Prem Selvaraj, Pratyush Kumar, Mitesh M. Khapra |
| 2022 | Adjoint-aided inference of Gaussian process driven differential equations. Paterne Gahungu, Christopher W. Lanyon, Mauricio A. Álvarez, Engineer Bainomugisha, Michael T. Smith, Richard Wilkinson |
| 2022 | Adv-Attribute: Inconspicuous and Transferable Adversarial Attack on Face Recognition. Shuai Jia, Bangjie Yin, Taiping Yao, Shouhong Ding, Chunhua Shen, Xiaokang Yang, Chao Ma |
| 2022 | Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022. Sanmi Koyejo, S. Mohamed, A. Agarwal, Danielle Belgrave, K. Cho, A. Oh |
| 2022 | Advancing Model Pruning via Bi-level Optimization. Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu |
| 2022 | Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks. Sizhe Chen, Zhehao Huang, Qinghua Tao, Yingwen Wu, Cihang Xie, Xiaolin Huang |
| 2022 | Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach. Kaiwen Yang, Yanchao Sun, Jiahao Su, Fengxiang He, Xinmei Tian, Furong Huang, Tianyi Zhou, Dacheng Tao |
| 2022 | Adversarial Reprogramming Revisited. Matthias Englert, Ranko Lazic |
| 2022 | Adversarial Robustness is at Odds with Lazy Training. Yunjuan Wang, Enayat Ullah, Poorya Mianjy, Raman Arora |
| 2022 | Adversarial Style Augmentation for Domain Generalized Urban-Scene Segmentation. Zhun Zhong, Yuyang Zhao, Gim Hee Lee, Nicu Sebe |
| 2022 | Adversarial Task Up-sampling for Meta-learning. Yichen Wu, Long-Kai Huang, Ying Wei |
| 2022 | Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks. Jianan Zhou, Jianing Zhu, Jingfeng Zhang, Tongliang Liu, Gang Niu, Bo Han, Masashi Sugiyama |
| 2022 | Adversarial Unlearning: Reducing Confidence Along Adversarial Directions. Amrith Setlur, Benjamin Eysenbach, Virginia Smith, Sergey Levine |
| 2022 | Adversarial training for high-stakes reliability. Daniel M. Ziegler, Seraphina Nix, Lawrence Chan, Tim Bauman, Peter Schmidt-Nielsen, Tao Lin, Adam Scherlis, Noa Nabeshima, Ben Weinstein-Raun, Daniel de Haas, Buck Shlegeris, Nate Thomas |
| 2022 | Adversarially Robust Learning: A Generic Minimax Optimal Learner and Characterization. Omar Montasser, Steve Hanneke, Nati Srebro |
| 2022 | AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph Generators. Wenkai Xu, Gesine D. Reinert |
| 2022 | Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift. Christina Baek, Yiding Jiang, Aditi Raghunathan, J. Zico Kolter |
| 2022 | AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier-Stokes Solutions. Florent Bonnet, Jocelyn Ahmed Mazari, Paola Cinnella, Patrick Gallinari |
| 2022 | Algorithms and Hardness for Learning Linear Thresholds from Label Proportions. Rishi Saket |
| 2022 | Algorithms that Approximate Data Removal: New Results and Limitations. Vinith M. Suriyakumar, Ashia C. Wilson |
| 2022 | Algorithms with Prediction Portfolios. Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Sergei Vassilvitskii |
| 2022 | Align then Fusion: Generalized Large-scale Multi-view Clustering with Anchor Matching Correspondences. Siwei Wang, Xinwang Liu, Suyuan Liu, Jiaqi Jin, Wenxuan Tu, Xinzhong Zhu, En Zhu |
| 2022 | Aligning individual brains with fused unbalanced Gromov Wasserstein. Alexis Thual, Quang Huy Tran, Tatiana Zemskova, Nicolas Courty, Rémi Flamary, Stanislas Dehaene, Bertrand Thirion |
| 2022 | Alignment-guided Temporal Attention for Video Action Recognition. Yizhou Zhao, Zhenyang Li, Xun Guo, Yan Lu |
| 2022 | All Politics is Local: Redistricting via Local Fairness. Shao-Heng Ko, Erin Taylor, Pankaj K. Agarwal, Kamesh Munagala |
| 2022 | Alleviating "Posterior Collapse" in Deep Topic Models via Policy Gradient. Yewen Li, Chaojie Wang, Zhibin Duan, Dongsheng Wang, Bo Chen, Bo An, Mingyuan Zhou |
| 2022 | Alleviating Adversarial Attacks on Variational Autoencoders with MCMC. Anna Kuzina, Max Welling, Jakub M. Tomczak |
| 2022 | Alleviating the Sample Selection Bias in Few-shot Learning by Removing Projection to the Centroid. Jing Xu, Xu Luo, Xinglin Pan, Yanan Li, Wenjie Pei, Zenglin Xu |
| 2022 | Alternating Mirror Descent for Constrained Min-Max Games. Andre Wibisono, Molei Tao, Georgios Piliouras |
| 2022 | Ambiguous Images With Human Judgments for Robust Visual Event Classification. Kate Sanders, Reno Kriz, Anqi Liu, Benjamin Van Durme |
| 2022 | Amortized Inference for Causal Structure Learning. Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf |
| 2022 | Amortized Inference for Heterogeneous Reconstruction in Cryo-EM. Axel Levy, Gordon Wetzstein, Julien N. P. Martel, Frédéric Poitevin, Ellen D. Zhong |
| 2022 | Amortized Mixing Coupling Processes for Clustering. Huafeng Liu, Liping Jing |
| 2022 | Amortized Projection Optimization for Sliced Wasserstein Generative Models. Khai Nguyen, Nhat Ho |
| 2022 | Amortized Proximal Optimization. Juhan Bae, Paul Vicol, Jeff Z. HaoChen, Roger B. Grosse |
| 2022 | Amplifying Membership Exposure via Data Poisoning. Yufei Chen, Chao Shen, Yun Shen, Cong Wang, Yang Zhang |
| 2022 | An $\alpha$-No-Regret Algorithm For Graphical Bilinear Bandits. Geovani Rizk, Igor Colin, Albert Thomas, Rida Laraki, Yann Chevaleyre |
| 2022 | An $\alpha$-regret analysis of Adversarial Bilateral Trade. Yossi Azar, Amos Fiat, Federico Fusco |
| 2022 | An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context. Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng, Pushi Zhang, Li Zhao, Wenxue Cheng, Peng Cheng, Yongqiang Xiong, Tao Qin, Jianyu Chen, Tie-Yan Liu |
| 2022 | An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects. Thanh Vinh Vo, Arnab Bhattacharyya, Young Lee, Tze-Yun Leong |
| 2022 | An Algorithm for Learning Switched Linear Dynamics from Data. Guillaume O. Berger, Monal Narasimhamurthy, Kandai Watanabe, Morteza Lahijanian, Sriram Sankaranarayanan |
| 2022 | An Analysis of Ensemble Sampling. Chao Qin, Zheng Wen, Xiuyuan Lu, Benjamin Van Roy |
| 2022 | An Analytical Theory of Curriculum Learning in Teacher-Student Networks. Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe |
| 2022 | An Asymptotically Optimal Batched Algorithm for the Dueling Bandit Problem. Arpit Agarwal, Rohan Ghuge, Viswanath Nagarajan |
| 2022 | An Embarrassingly Simple Approach to Semi-Supervised Few-Shot Learning. Xiu-Shen Wei, He-Yang Xu, Faen Zhang, Yuxin Peng, Wei Zhou |
| 2022 | An Empirical Study on Disentanglement of Negative-free Contrastive Learning. Jinkun Cao, Ruiqian Nai, Qing Yang, Jialei Huang, Yang Gao |
| 2022 | An In-depth Study of Stochastic Backpropagation. Jun Fang, Mingze Xu, Hao Chen, Bing Shuai, Zhuowen Tu, Joseph Tighe |
| 2022 | An Information-Theoretic Framework for Deep Learning. Hong Jun Jeon, Benjamin Van Roy |
| 2022 | An Investigation into Whitening Loss for Self-supervised Learning. Xi Weng, Lei Huang, Lei Zhao, Rao Muhammad Anwer, Salman H. Khan, Fahad Shahbaz Khan |
| 2022 | An efficient graph generative model for navigating ultra-large combinatorial synthesis libraries. Aryan Pedawi, Pawel Gniewek, Chaoyi Chang, Brandon M. Anderson, Henry van den Bedem |
| 2022 | An empirical analysis of compute-optimal large language model training. Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de Las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, Tom Hennigan, Eric Noland, Katherine Millican, George van den Driessche, Bogdan Damoc, Aurelia Guy, Simon Osindero, Karen Simonyan, Erich Elsen, Oriol Vinyals, Jack W. Rae, Laurent Sifre |
| 2022 | Analyzing Data-Centric Properties for Graph Contrastive Learning. Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan |
| 2022 | Analyzing Lottery Ticket Hypothesis from PAC-Bayesian Theory Perspective. Keitaro Sakamoto, Issei Sato |
| 2022 | Analyzing Sharpness along GD Trajectory: Progressive Sharpening and Edge of Stability. Zixuan Wang, Zhouzi Li, Jian Li |
| 2022 | Anchor-Changing Regularized Natural Policy Gradient for Multi-Objective Reinforcement Learning. Ruida Zhou, Tao Liu, Dileep Kalathil, P. R. Kumar, Chao Tian |
| 2022 | AniFaceGAN: Animatable 3D-Aware Face Image Generation for Video Avatars. Yue Wu, Yu Deng, Jiaolong Yang, Fangyun Wei, Qifeng Chen, Xin Tong |
| 2022 | AnimeRun: 2D Animation Visual Correspondence from Open Source 3D Movies. Li Siyao, Yuhang Li, Bo Li, Chao Dong, Ziwei Liu, Chen Change Loy |
| 2022 | AnimeSR: Learning Real-World Super-Resolution Models for Animation Videos. Yanze Wu, Xintao Wang, Gen Li, Ying Shan |
| 2022 | Annihilation of Spurious Minima in Two-Layer ReLU Networks. Yossi Arjevani, Michael Field |
| 2022 | AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection. Marius Dragoi, Elena Burceanu, Emanuela Haller, Andrei Manolache, Florin Brad |
| 2022 | Anonymized Histograms in Intermediate Privacy Models. Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi |
| 2022 | Anonymous Bandits for Multi-User Systems. Hossein Esfandiari, Vahab Mirrokni, Jon Schneider |
| 2022 | Anticipating Performativity by Predicting from Predictions. Celestine Mendler-Dünner, Frances Ding, Yixin Wang |
| 2022 | Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures. Shitong Luo, Yufeng Su, Xingang Peng, Sheng Wang, Jian Peng, Jianzhu Ma |
| 2022 | Anytime-Valid Inference For Multinomial Count Data. Michael Lindon, Alan Malek |
| 2022 | Approaching Quartic Convergence Rates for Quasi-Stochastic Approximation with Application to Gradient-Free Optimization. Caio Kalil Lauand, Sean P. Meyn |
| 2022 | Approximate Euclidean lengths and distances beyond Johnson-Lindenstrauss. Aleksandros Sobczyk, Mathieu Luisier |
| 2022 | Approximate Secular Equations for the Cubic Regularization Subproblem. Yihang Gao, Man-Chung Yue, Michael Ng |
| 2022 | Approximate Value Equivalence. Christopher Grimm, André Barreto, Satinder Singh |
| 2022 | Approximation with CNNs in Sobolev Space: with Applications to Classification. Guohao Shen, Yuling Jiao, Yuanyuan Lin, Jian Huang |
| 2022 | Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions. Omri Ben-Eliezer, Dan Mikulincer, Ilias Zadik |
| 2022 | Are All Losses Created Equal: A Neural Collapse Perspective. Jinxin Zhou, Chong You, Xiao Li, Kangning Liu, Sheng Liu, Qing Qu, Zhihui Zhu |
| 2022 | Are AlphaZero-like Agents Robust to Adversarial Perturbations? Li-Cheng Lan, Huan Zhang, Ti-Rong Wu, Meng-Yu Tsai, I-Chen Wu, Cho-Jui Hsieh |
| 2022 | Are Defenses for Graph Neural Networks Robust? Felix Mujkanovic, Simon Geisler, Stephan Günnemann, Aleksandar Bojchevski |
| 2022 | Are GANs overkill for NLP? David Alvarez-Melis, Vikas Garg, Adam Kalai |
| 2022 | Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural Networks. Michael Lohaus, Matthäus Kleindessner, Krishnaram Kenthapadi, Francesco Locatello, Chris Russell |
| 2022 | Are You Stealing My Model? Sample Correlation for Fingerprinting Deep Neural Networks. Jiyang Guan, Jian Liang, Ran He |
| 2022 | Are all Frames Equal? Active Sparse Labeling for Video Action Detection. Aayush Jung Rana, Yogesh S. Rawat |
| 2022 | Ask4Help: Learning to Leverage an Expert for Embodied Tasks. Kunal Pratap Singh, Luca Weihs, Alvaro Herrasti, Jonghyun Choi, Aniruddha Kembhavi, Roozbeh Mottaghi |
| 2022 | Assaying Out-Of-Distribution Generalization in Transfer Learning. Florian Wenzel, Andrea Dittadi, Peter V. Gehler, Carl-Johann Simon-Gabriel, Max Horn, Dominik Zietlow, David Kernert, Chris Russell, Thomas Brox, Bernt Schiele, Bernhard Schölkopf, Francesco Locatello |
| 2022 | Assistive Teaching of Motor Control Tasks to Humans. Megha Srivastava, Erdem Biyik, Suvir Mirchandani, Noah D. Goodman, Dorsa Sadigh |
| 2022 | Associating Objects and Their Effects in Video through Coordination Games. Erika Lu, Forrester Cole, Weidi Xie, Tali Dekel, Bill Freeman, Andrew Zisserman, Michael Rubinstein |
| 2022 | Association Graph Learning for Multi-Task Classification with Category Shifts. Jiayi Shen, Zehao Xiao, Xiantong Zhen, Cees Snoek, Marcel Worring |
| 2022 | Asymmetric Temperature Scaling Makes Larger Networks Teach Well Again. Xin-Chun Li, Wen-Shu Fan, Shaoming Song, Yinchuan Li, Bingshuai Li, Yunfeng Shao, De-Chuan Zhan |
| 2022 | Asymptotic Behaviors of Projected Stochastic Approximation: A Jump Diffusion Perspective. Jiadong Liang, Yuze Han, Xiang Li, Zhihua Zhang |
| 2022 | Asymptotic Properties for Bayesian Neural Network in Besov Space. Kyeongwon Lee, Jaeyong Lee |
| 2022 | Asymptotically Unbiased Instance-wise Regularized Partial AUC Optimization: Theory and Algorithm. Huiyang Shao, Qianqian Xu, Zhiyong Yang, Shilong Bao, Qingming Huang |
| 2022 | Asymptotics of smoothed Wasserstein distances in the small noise regime. Yunzi Ding, Jonathan Niles-Weed |
| 2022 | Asymptotics of ℓ Andrew Davison |
| 2022 | Asynchronous Actor-Critic for Multi-Agent Reinforcement Learning. Yuchen Xiao, Weihao Tan, Christopher Amato |
| 2022 | Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays. Konstantin Mishchenko, Francis R. Bach, Mathieu Even, Blake E. Woodworth |
| 2022 | AttCAT: Explaining Transformers via Attentive Class Activation Tokens. Yao Qiang, Deng Pan, Chengyin Li, Xin Li, Rhongho Jang, Dongxiao Zhu |
| 2022 | Attention-based Neural Cellular Automata. Mattie Tesfaldet, Derek Nowrouzezahrai, Chris Pal |
| 2022 | Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation. Shiqi Yang, Yaxing Wang, Kai Wang, Shangling Jui, Joost van de Weijer |
| 2022 | Audio-Driven Co-Speech Gesture Video Generation. Xian Liu, Qianyi Wu, Hang Zhou, Yuanqi Du, Wayne Wu, Dahua Lin, Ziwei Liu |
| 2022 | Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative. Tianxin Wei, Yuning You, Tianlong Chen, Yang Shen, Jingrui He, Zhangyang Wang |
| 2022 | Augmented RBMLE-UCB Approach for Adaptive Control of Linear Quadratic Systems. Akshay Mete, Rahul Singh, P. R. Kumar |
| 2022 | Augmenting Online Algorithms with $\varepsilon$-Accurate Predictions. Anupam Gupta, Debmalya Panigrahi, Bernardo Subercaseaux, Kevin Sun |
| 2022 | AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking Keypoints. Xingzhe He, Bastian Wandt, Helge Rhodin |
| 2022 | AutoML Two-Sample Test. Jonas M. Kübler, Vincent Stimper, Simon Buchholz, Krikamol Muandet, Bernhard Schölkopf |
| 2022 | AutoMS: Automatic Model Selection for Novelty Detection with Error Rate Control. Yifan Zhang, Haiyan Jiang, Haojie Ren, Changliang Zou, Dejing Dou |
| 2022 | AutoMTL: A Programming Framework for Automating Efficient Multi-Task Learning. Lijun Zhang, Xiao Liu, Hui Guan |
| 2022 | AutoST: Towards the Universal Modeling of Spatio-temporal Sequences. Jianxin Li, Shuai Zhang, Hui Xiong, Haoyi Zhou |
| 2022 | AutoWS-Bench-101: Benchmarking Automated Weak Supervision with 100 Labels. Nicholas Carl Roberts, Xintong Li, Tzu-Heng Huang, Dyah Adila, Spencer Schoenberg, Cheng-Yu Liu, Lauren Pick, Haotian Ma, Aws Albarghouthi, Frederic Sala |
| 2022 | Autoformalization with Large Language Models. Yuhuai Wu, Albert Qiaochu Jiang, Wenda Li, Markus N. Rabe, Charles Staats, Mateja Jamnik, Christian Szegedy |
| 2022 | Autoinverse: Uncertainty Aware Inversion of Neural Networks. Navid Ansari, Hans-Peter Seidel, Nima Vahidi Ferdowsi, Vahid Babaei |
| 2022 | Automatic Differentiation of Programs with Discrete Randomness. Gaurav Arya, Moritz Schauer, Frank Schäfer, Christopher Rackauckas |
| 2022 | Automatic differentiation of nonsmooth iterative algorithms. Jérôme Bolte, Edouard Pauwels, Samuel Vaiter |
| 2022 | Autoregressive Perturbations for Data Poisoning. Pedro Sandoval Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein, David Jacobs |
| 2022 | Autoregressive Search Engines: Generating Substrings as Document Identifiers. Michele Bevilacqua, Giuseppe Ottaviano, Patrick Lewis, Scott Yih, Sebastian Riedel, Fabio Petroni |
| 2022 | Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worlds. Joshua Albrecht, Abraham J. Fetterman, Bryden Fogelman, Ellie Kitanidis, Bartosz Wróblewski, Nicole Seo, Michael Rosenthal, Maksis Knutins, Zack Polizzi, James Simon, Kanjun Qiu |
| 2022 | Average Sensitivity of Euclidean k-Clustering. Yuichi Yoshida, Shinji Ito |
| 2022 | BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression. Haoyu Zhao, Boyue Li, Zhize Li, Peter Richtárik, Yuejie Chi |
| 2022 | BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework. Tingting Liang, Hongwei Xie, Kaicheng Yu, Zhongyu Xia, Zhiwei Lin, Yongtao Wang, Tao Tang, Bing Wang, Zhi Tang |
| 2022 | BILCO: An Efficient Algorithm for Joint Alignment of Time Series. Xuelong Mi, Mengfan Wang, Alex Bo-Yuan Chen, Jing-Xuan Lim, Yizhi Wang, Misha B. Ahrens, Guoqiang Yu |
| 2022 | BLOX: Macro Neural Architecture Search Benchmark and Algorithms. Thomas Chau, Lukasz Dudziak, Hongkai Wen, Nicholas D. Lane, Mohamed S. Abdelfattah |
| 2022 | BMU-MoCo: Bidirectional Momentum Update for Continual Video-Language Modeling. Yizhao Gao, Nanyi Fei, Haoyu Lu, Zhiwu Lu, Hao Jiang, Yijie Li, Zhao Cao |
| 2022 | BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach. Bo Liu, Mao Ye, Stephen Wright, Peter Stone, Qiang Liu |
| 2022 | BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs. Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu |
| 2022 | BR-SNIS: Bias Reduced Self-Normalized Importance Sampling. Gabriel Cardoso, Sergey Samsonov, Achille Thin, Eric Moulines, Jimmy Olsson |
| 2022 | BYOL-Explore: Exploration by Bootstrapped Prediction. Zhaohan Guo, Shantanu Thakoor, Miruna Pislar, Bernardo Ávila Pires, Florent Altché, Corentin Tallec, Alaa Saade, Daniele Calandriello, Jean-Bastien Grill, Yunhao Tang, Michal Valko, Rémi Munos, Mohammad Gheshlaghi Azar, Bilal Piot |
| 2022 | Back Razor: Memory-Efficient Transfer Learning by Self-Sparsified Backpropagation. Ziyu Jiang, Xuxi Chen, Xueqin Huang, Xianzhi Du, Denny Zhou, Zhangyang Wang |
| 2022 | BackdoorBench: A Comprehensive Benchmark of Backdoor Learning. Baoyuan Wu, Hongrui Chen, Mingda Zhang, Zihao Zhu, Shaokui Wei, Danni Yuan, Chao Shen |
| 2022 | BadPrompt: Backdoor Attacks on Continuous Prompts. Xiangrui Cai, Haidong Xu, Sihan Xu, Ying Zhang, Xiaojie Yuan |
| 2022 | BagFlip: A Certified Defense Against Data Poisoning. Yuhao Zhang, Aws Albarghouthi, Loris D'Antoni |
| 2022 | Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization. Hui Yuan, Chengzhuo Ni, Huazheng Wang, Xuezhou Zhang, Le Cong, Csaba Szepesvári, Mengdi Wang |
| 2022 | Batch Bayesian Optimization on Permutations using the Acquisition Weighted Kernel. ChangYong Oh, Roberto Bondesan, Efstratios Gavves, Max Welling |
| 2022 | Batch Bayesian optimisation via density-ratio estimation with guarantees. Rafael Oliveira, Louis C. Tiao, Fabio T. Ramos |
| 2022 | Batch Multi-Fidelity Active Learning with Budget Constraints. Shibo Li, Jeff M. Phillips, Xin Yu, Robert M. Kirby, Shandian Zhe |
| 2022 | Batch size-invariance for policy optimization. Jacob Hilton, Karl Cobbe, John Schulman |
| 2022 | Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms. Xutong Liu, Jinhang Zuo, Siwei Wang, Carlee Joe-Wong, John C. S. Lui, Wei Chen |
| 2022 | BayesPCN: A Continually Learnable Predictive Coding Associative Memory. Jinsoo Yoo, Frank Wood |
| 2022 | Bayesian Active Learning with Fully Bayesian Gaussian Processes. Christoffer Riis, Francisco Antunes, Frederik Boe Hüttel, Carlos Lima Azevedo, Francisco Pereira |
| 2022 | Bayesian Clustering of Neural Spiking Activity Using a Mixture of Dynamic Poisson Factor Analyzers. Ganchao Wei, Ian H. Stevenson, Xiaojing Wang |
| 2022 | Bayesian Optimistic Optimization: Optimistic Exploration for Model-based Reinforcement Learning. Chenyang Wu, Tianci Li, Zongzhang Zhang, Yang Yu |
| 2022 | Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization. Samuel Daulton, Xingchen Wan, David Eriksson, Maximilian Balandat, Michael A. Osborne, Eytan Bakshy |
| 2022 | Bayesian Persuasion for Algorithmic Recourse. Keegan Harris, Valerie Chen, Joon Sik Kim, Ameet Talwalkar, Hoda Heidari, Zhiwei Steven Wu |
| 2022 | Bayesian Risk Markov Decision Processes. Yifan Lin, Yuxuan Ren, Enlu Zhou |
| 2022 | Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty. Luning Sun, Daniel Huang, Hao Sun, Jian-Xun Wang |
| 2022 | Bayesian inference via sparse Hamiltonian flows. Naitong Chen, Zuheng Xu, Trevor Campbell |
| 2022 | Behavior Transformers: Cloning $k$ modes with one stone. Nur Muhammad Shafiullah, Zichen Jeff Cui, Ariuntuya Altanzaya, Lerrel Pinto |
| 2022 | Bellman Residual Orthogonalization for Offline Reinforcement Learning. Andrea Zanette, Martin J. Wainwright |
| 2022 | Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability. Jonathan Crabbé, Alicia Curth, Ioana Bica, Mihaela van der Schaar |
| 2022 | Benchmarking and Analyzing 3D Human Pose and Shape Estimation Beyond Algorithms. Hui En Pang, Zhongang Cai, Lei Yang, Tianwei Zhang, Ziwei Liu |
| 2022 | Benchopt: Reproducible, efficient and collaborative optimization benchmarks. Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupré la Tour, Ghislain Durif, Cássio F. Dantas, Quentin Klopfenstein, Johan Larsson, En Lai, Tanguy Lefort, Benoît Malézieux, Badr Moufad, Binh T. Nguyen, Alain Rakotomamonjy, Zaccharie Ramzi, Joseph Salmon, Samuel Vaiter |
| 2022 | Benefits of Additive Noise in Composing Classes with Bounded Capacity. Alireza Fathollah Pour, Hassan Ashtiani |
| 2022 | Benefits of Permutation-Equivariance in Auction Mechanisms. Tian Qin, Fengxiang He, Dingfeng Shi, Wenbing Huang, Dacheng Tao |
| 2022 | Benign Overfitting in Two-layer Convolutional Neural Networks. Yuan Cao, Zixiang Chen, Misha Belkin, Quanquan Gu |
| 2022 | Benign Underfitting of Stochastic Gradient Descent. Tomer Koren, Roi Livni, Yishay Mansour, Uri Sherman |
| 2022 | Benign, Tempered, or Catastrophic: Toward a Refined Taxonomy of Overfitting. Neil Mallinar, James B. Simon, Amirhesam Abedsoltan, Parthe Pandit, Mikhail Belkin, Preetum Nakkiran |
| 2022 | Bessel Equivariant Networks for Inversion of Transmission Effects in Multi-Mode Optical Fibres. Joshua Mitton, Simon Peter Mekhail, Miles J. Padgett, Daniele Faccio, Marco Aversa, Roderick Murray-Smith |
| 2022 | Best of Both Worlds Model Selection. Aldo Pacchiano, Christoph Dann, Claudio Gentile |
| 2022 | Better Best of Both Worlds Bounds for Bandits with Switching Costs. Idan Amir, Guy Azov, Tomer Koren, Roi Livni |
| 2022 | Better SGD using Second-order Momentum. Hoang Tran, Ashok Cutkosky |
| 2022 | Better Uncertainty Calibration via Proper Scores for Classification and Beyond. Sebastian G. Gruber, Florian Buettner |
| 2022 | Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness. Sarah Sachs, Hédi Hadiji, Tim van Erven, Cristóbal Guzmán |
| 2022 | Beyond Adult and COMPAS: Fair Multi-Class Prediction via Information Projection. Wael Alghamdi, Hsiang Hsu, Haewon Jeong, Hao Wang, Peter Michalák, Shahab Asoodeh, Flávio P. Calmon |
| 2022 | Beyond IID: data-driven decision-making in heterogeneous environments. Omar Besbes, Will Ma, Omar Mouchtaki |
| 2022 | Beyond L1: Faster and Better Sparse Models with skglm. Quentin Bertrand, Quentin Klopfenstein, Pierre-Antoine Bannier, Gauthier Gidel, Mathurin Massias |
| 2022 | Beyond Mahalanobis Distance for Textual OOD Detection. Pierre Colombo, Eduardo Dadalto Câmara Gomes, Guillaume Staerman, Nathan Noiry, Pablo Piantanida |
| 2022 | Beyond Not-Forgetting: Continual Learning with Backward Knowledge Transfer. Sen Lin, Li Yang, Deliang Fan, Junshan Zhang |
| 2022 | Beyond Real-world Benchmark Datasets: An Empirical Study of Node Classification with GNNs. Seiji Maekawa, Koki Noda, Yuya Sasaki, Makoto Onizuka |
| 2022 | Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis. Shayegan Omidshafiei, Andrei Kapishnikov, Yannick Assogba, Lucas Dixon, Been Kim |
| 2022 | Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations. Jeff Z. HaoChen, Colin Wei, Ananya Kumar, Tengyu Ma |
| 2022 | Beyond Time-Average Convergence: Near-Optimal Uncoupled Online Learning via Clairvoyant Multiplicative Weights Update. Georgios Piliouras, Ryann Sim, Stratis Skoulakis |
| 2022 | Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules. Yuhan Helena Liu, Arna Ghosh, Blake A. Richards, Eric Shea-Brown, Guillaume Lajoie |
| 2022 | Beyond black box densities: Parameter learning for the deviated components. Dat Do, Nhat Ho, XuanLong Nguyen |
| 2022 | Beyond neural scaling laws: beating power law scaling via data pruning. Ben Sorscher, Robert Geirhos, Shashank Shekhar, Surya Ganguli, Ari Morcos |
| 2022 | Beyond spectral gap: the role of the topology in decentralized learning. Thijs Vogels, Hadrien Hendrikx, Martin Jaggi |
| 2022 | Beyond the Best: Distribution Functional Estimation in Infinite-Armed Bandits. Yifei Wang, Tavor Z. Baharav, Yanjun Han, Jiantao Jiao, David Tse |
| 2022 | Beyond the Return: Off-policy Function Estimation under User-specified Error-measuring Distributions. Audrey Huang, Nan Jiang |
| 2022 | Bezier Gaussian Processes for Tall and Wide Data. Martin Jørgensen, Michael A. Osborne |
| 2022 | Bi-directional Weakly Supervised Knowledge Distillation for Whole Slide Image Classification. Linhao Qu, Xiaoyuan Luo, Manning Wang, Zhijian Song |
| 2022 | BiMLP: Compact Binary Architectures for Vision Multi-Layer Perceptrons. Yixing Xu, Xinghao Chen, Yunhe Wang |
| 2022 | BiT: Robustly Binarized Multi-distilled Transformer. Zechun Liu, Barlas Oguz, Aasish Pappu, Lin Xiao, Scott Yih, Meng Li, Raghuraman Krishnamoorthi, Yashar Mehdad |
| 2022 | Bidirectional Learning for Offline Infinite-width Model-based Optimization. Can Chen, Yingxue Zhang, Jie Fu, Xue (Steve) Liu, Mark Coates |
| 2022 | BigBio: A Framework for Data-Centric Biomedical Natural Language Processing. Jason A. Fries, Leon Weber, Natasha Seelam, Gabriel Altay, Debajyoti Datta, Samuele Garda, Sunny Kang, Rosaline Su, Wojciech Kusa, Samuel Cahyawijaya, Fabio Barth, Simon Ott, Matthias Samwald, Stephen H. Bach, Stella Biderman, Mario Sänger, Bo Wang, Alison Callahan, Daniel León Periñán, Théo Gigant, Patrick Haller, Jenny Chim, José D. Posada, John M. Giorgi, Karthik Rangasai Sivaraman, Marc Pàmies, Marianna Nezhurina, Robert Martin, Michael Cullan, Moritz Freidank, Nathan Dahlberg, Shubhanshu Mishra, Shamik Bose, Nicholas Broad, Yanis Labrak, Shlok Deshmukh, Sid Kiblawi, Ayush Singh, Minh Chien Vu, Trishala Neeraj, Jonas Golde, Albert Villanova del Moral, Benjamin Beilharz |
| 2022 | BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis. Yichong Leng, Zehua Chen, Junliang Guo, Haohe Liu, Jiawei Chen, Xu Tan, Danilo P. Mandic, Lei He, Xiangyang Li, Tao Qin, Sheng Zhao, Tie-Yan Liu |
| 2022 | Biological Learning of Irreducible Representations of Commuting Transformations. Alexander Genkin, David Lipshutz, Siavash Golkar, Tiberiu Tesileanu, Dmitri B. Chklovskii |
| 2022 | Biologically Inspired Dynamic Thresholds for Spiking Neural Networks. Jianchuan Ding, Bo Dong, Felix Heide, Yufei Ding, Yunduo Zhou, Baocai Yin, Xin Yang |
| 2022 | Biologically plausible solutions for spiking networks with efficient coding. Veronika Koren, Stefano Panzeri |
| 2022 | Biologically-Plausible Determinant Maximization Neural Networks for Blind Separation of Correlated Sources. Bariscan Bozkurt, Cengiz Pehlevan, Alper T. Erdogan |
| 2022 | Biologically-plausible backpropagation through arbitrary timespans via local neuromodulators. Yuhan Helena Liu, Stephen Smith, Stefan Mihalas, Eric Shea-Brown, Uygar Sümbül |
| 2022 | Bivariate Causal Discovery for Categorical Data via Classification with Optimal Label Permutation. Yang Ni |
| 2022 | Black-Box Generalization: Stability of Zeroth-Order Learning. Konstantinos E. Nikolakakis, Farzin Haddadpour, Dionysios S. Kalogerias, Amin Karbasi |
| 2022 | Black-box coreset variational inference. Dionysis Manousakas, Hippolyt Ritter, Theofanis Karaletsos |
| 2022 | Blackbox Attacks via Surrogate Ensemble Search. Zikui Cai, Chengyu Song, Srikanth V. Krishnamurthy, Amit Roy-Chowdhury, Salman Asif |
| 2022 | Blessing of Depth in Linear Regression: Deeper Models Have Flatter Landscape Around the True Solution. Jianhao Ma, Salar Fattahi |
| 2022 | Block-Recurrent Transformers. DeLesley Hutchins, Imanol Schlag, Yuhuai Wu, Ethan Dyer, Behnam Neyshabur |
| 2022 | Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness. Avrim Blum, Omar Montasser, Greg Shakhnarovich, Hongyang Zhang |
| 2022 | Boosting Out-of-distribution Detection with Typical Features. Yao Zhu, Yuefeng Chen, Chuanlong Xie, Xiaodan Li, Rong Zhang, Hui Xue, Xiang Tian, Bolun Zheng, Yaowu Chen |
| 2022 | Boosting the Performance of Generic Deep Neural Network Frameworks with Log-supermodular CRFs. Hao Xiong, Yangxiao Lu, Nicholas Ruozzi |
| 2022 | Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation. Zeyu Qin, Yanbo Fan, Yi Liu, Li Shen, Yong Zhang, Jue Wang, Baoyuan Wu |
| 2022 | Bootstrapped Transformer for Offline Reinforcement Learning. Kerong Wang, Hanye Zhao, Xufang Luo, Kan Ren, Weinan Zhang, Dongsheng Li |
| 2022 | Bounded-Regret MPC via Perturbation Analysis: Prediction Error, Constraints, and Nonlinearity. Yiheng Lin, Yang Hu, Guannan Qu, Tongxin Li, Adam Wierman |
| 2022 | Bounding and Approximating Intersectional Fairness through Marginal Fairness. Mathieu Molina, Patrick Loiseau |
| 2022 | Brain Network Transformer. Xuan Kan, Wei Dai, Hejie Cui, Zilong Zhang, Ying Guo, Carl Yang |
| 2022 | Branch & Learn for Recursively and Iteratively Solvable Problems in Predict+Optimize. Xinyi Hu, Jasper C. H. Lee, Jimmy H. M. Lee, Allen Z. Zhong |
| 2022 | Breaking Bad: A Dataset for Geometric Fracture and Reassembly. Silvia Sellán, Yun-Chun Chen, Ziyi Wu, Animesh Garg, Alec Jacobson |
| 2022 | Bridge the Gap Between Architecture Spaces via A Cross-Domain Predictor. Yuqiao Liu, Yehui Tang, Zeqiong Lv, Yunhe Wang, Yanan Sun |
| 2022 | Bridging Central and Local Differential Privacy in Data Acquisition Mechanisms. Alireza Fallah, Ali Makhdoumi, Azarakhsh Malekian, Asuman E. Ozdaglar |
| 2022 | Bridging the Gap Between Vision Transformers and Convolutional Neural Networks on Small Datasets. Zhiying Lu, Hongtao Xie, Chuanbin Liu, Yongdong Zhang |
| 2022 | Bridging the Gap between Object and Image-level Representations for Open-Vocabulary Detection. Hanoona Abdul Rasheed, Muhammad Maaz, Muhammad Uzair Khattak, Salman H. Khan, Fahad Shahbaz Khan |
| 2022 | Bridging the Gap from Asymmetry Tricks to Decorrelation Principles in Non-contrastive Self-supervised Learning. Kang-Jun Liu, Masanori Suganuma, Takayuki Okatani |
| 2022 | Bridging the Gap: Unifying the Training and Evaluation of Neural Network Binary Classifiers. Nathan Tsoi, Kate Candon, Deyuan Li, Yofti Milkessa, Marynel Vázquez |
| 2022 | Bring Your Own Algorithm for Optimal Differentially Private Stochastic Minimax Optimization. Liang Zhang, Kiran Koshy Thekumparampil, Sewoong Oh, Niao He |
| 2022 | Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens. Elad Ben-Avraham, Roei Herzig, Karttikeya Mangalam, Amir Bar, Anna Rohrbach, Leonid Karlinsky, Trevor Darrell, Amir Globerson |
| 2022 | Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints. Justin Whitehouse, Aaditya Ramdas, Zhiwei Steven Wu, Ryan M. Rogers |
| 2022 | Byzantine Spectral Ranking. Arnhav Datar, Arun Rajkumar, John Augustine |
| 2022 | Byzantine-tolerant federated Gaussian process regression for streaming data. Xu Zhang, Zhenyuan Yuan, Minghui Zhu |
| 2022 | C-Mixup: Improving Generalization in Regression. Huaxiu Yao, Yiping Wang, Linjun Zhang, James Y. Zou, Chelsea Finn |
| 2022 | C2FAR: Coarse-to-Fine Autoregressive Networks for Precise Probabilistic Forecasting. Shane Bergsma, Timothy Zeyl, Javad Rahimipour Anaraki, Lei Guo |
| 2022 | CAESAR: An Embodied Simulator for Generating Multimodal Referring Expression Datasets. Md Mofijul Islam, Reza Mirzaiee, Alexi Gladstone, Haley N. Green, Tariq Iqbal |
| 2022 | CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds. Haiyang Wang, Lihe Ding, Shaocong Dong, Shaoshuai Shi, Aoxue Li, Jianan Li, Zhenguo Li, Liwei Wang |
| 2022 | CARD: Classification and Regression Diffusion Models. Xizewen Han, Huangjie Zheng, Mingyuan Zhou |
| 2022 | CARLANE: A Lane Detection Benchmark for Unsupervised Domain Adaptation from Simulation to multiple Real-World Domains. Bonifaz Stuhr, Johann Haselberger, Julian Gebele |
| 2022 | CASA: Category-agnostic Skeletal Animal Reconstruction. Yuefan Wu, Zeyuan Chen, Shaowei Liu, Zhongzheng Ren, Shenlong Wang |
| 2022 | CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks. Xuanli He, Qiongkai Xu, Yi Zeng, Lingjuan Lyu, Fangzhao Wu, Jiwei Li, Ruoxi Jia |
| 2022 | CCCP is Frank-Wolfe in disguise. Alp Yurtsever, Suvrit Sra |
| 2022 | CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior. Eldar David Abraham, Karel D'Oosterlinck, Amir Feder, Yair Ori Gat, Atticus Geiger, Christopher Potts, Roi Reichart, Zhengxuan Wu |
| 2022 | CEDe: A collection of expert-curated datasets with atom-level entity annotations for Optical Chemical Structure Recognition. Rodrigo Hormazabal, Changyoung Park, Soonyoung Lee, Sehui Han, Yeonsik Jo, Jaewan Lee, Ahra Jo, Seung Hwan Kim, Jaegul Choo, Moontae Lee, Honglak Lee |
| 2022 | CEIP: Combining Explicit and Implicit Priors for Reinforcement Learning with Demonstrations. Kai Yan, Alexander G. Schwing, Yu-Xiong Wang |
| 2022 | CGLB: Benchmark Tasks for Continual Graph Learning. Xikun Zhang, Dongjin Song, Dacheng Tao |
| 2022 | CHIMLE: Conditional Hierarchical IMLE for Multimodal Conditional Image Synthesis. Shichong Peng, Seyed Alireza Moazenipourasil, Ke Li |
| 2022 | CLEAR: Generative Counterfactual Explanations on Graphs. Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li |
| 2022 | CLEVRER-Humans: Describing Physical and Causal Events the Human Way. Jiayuan Mao, Xuelin Yang, Xikun Zhang, Noah D. Goodman, Jiajun Wu |
| 2022 | CLIPDraw: Exploring Text-to-Drawing Synthesis through Language-Image Encoders. Kevin Frans, Lisa B. Soros, Olaf Witkowski |
| 2022 | CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP. Andreas Fürst, Elisabeth Rumetshofer, Johannes Lehner, Viet T. Tran, Fei Tang, Hubert Ramsauer, David P. Kreil, Michael Kopp, Günter Klambauer, Angela Bitto, Sepp Hochreiter |
| 2022 | CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks. Tejas Srinivasan, Ting-Yun Chang, Leticia Leonor Pinto Alva, Georgios Chochlakis, Mohammad Rostami, Jesse Thomason |
| 2022 | COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics. Lianhui Qin, Sean Welleck, Daniel Khashabi, Yejin Choi |
| 2022 | CS-Shapley: Class-wise Shapley Values for Data Valuation in Classification. Stephanie Schoch, Haifeng Xu, Yangfeng Ji |
| 2022 | CUP: Critic-Guided Policy Reuse. Jin Zhang, Siyuan Li, Chongjie Zhang |
| 2022 | Cache-Augmented Inbatch Importance Resampling for Training Recommender Retriever. Jin Chen, Defu Lian, Yucheng Li, Baoyun Wang, Kai Zheng, Enhong Chen |
| 2022 | CageNeRF: Cage-based Neural Radiance Field for Generalized 3D Deformation and Animation. Yicong Peng, Yichao Yan, Shengqi Liu, Yuhao Cheng, Shanyan Guan, Bowen Pan, Guangtao Zhai, Xiaokang Yang |
| 2022 | CalFAT: Calibrated Federated Adversarial Training with Label Skewness. Chen Chen, Yuchen Liu, Xingjun Ma, Lingjuan Lyu |
| 2022 | Calibrated Data-Dependent Constraints with Exact Satisfaction Guarantees. Songkai Xue, Yuekai Sun, Mikhail Yurochkin |
| 2022 | Can Adversarial Training Be Manipulated By Non-Robust Features? Lue Tao, Lei Feng, Hongxin Wei, Jinfeng Yi, Sheng-Jun Huang, Songcan Chen |
| 2022 | Can Hybrid Geometric Scattering Networks Help Solve the Maximum Clique Problem? Yimeng Min, Frederik Wenkel, Michael Perlmutter, Guy Wolf |
| 2022 | Can Push-forward Generative Models Fit Multimodal Distributions? Antoine Salmona, Valentin De Bortoli, Julie Delon, Agnès Desolneux |
| 2022 | Capturing Failures of Large Language Models via Human Cognitive Biases. Erik Jones, Jacob Steinhardt |
| 2022 | Capturing Graphs with Hypo-Elliptic Diffusions. Csaba Tóth, Darrick Lee, Celia Hacker, Harald Oberhauser |
| 2022 | CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label Classification. Siddhant Kharbanda, Atmadeep Banerjee, Erik Schultheis, Rohit Babbar |
| 2022 | Category-Level 6D Object Pose Estimation in the Wild: A Semi-Supervised Learning Approach and A New Dataset. Yanjie Ze, Xiaolong Wang |
| 2022 | Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis. Ronan Perry, Julius von Kügelgen, Bernhard Schölkopf |
| 2022 | Causal Discovery in Linear Latent Variable Models Subject to Measurement Error. Yuqin Yang, AmirEmad Ghassami, Mohamed S. Nafea, Negar Kiyavash, Kun Zhang, Ilya Shpitser |
| 2022 | Causal Identification under Markov equivalence: Calculus, Algorithm, and Completeness. Amin Jaber, Adèle H. Ribeiro, Jiji Zhang, Elias Bareinboim |
| 2022 | Causal Inference with Non-IID Data using Linear Graphical Models. Chi Zhang, Karthika Mohan, Judea Pearl |
| 2022 | Causality Preserving Chaotic Transformation and Classification using Neurochaos Learning. Harikrishnan N. B., Aditi Kathpalia, Nithin Nagaraj |
| 2022 | Causality-driven Hierarchical Structure Discovery for Reinforcement Learning. Shaohui Peng, Xing Hu, Rui Zhang, Ke Tang, Jiaming Guo, Qi Yi, Ruizhi Chen, Xishan Zhang, Zidong Du, Ling Li, Qi Guo, Yunji Chen |
| 2022 | Causally motivated multi-shortcut identification and removal. Jiayun Zheng, Maggie Makar |
| 2022 | Censored Quantile Regression Neural Networks for Distribution-Free Survival Analysis. Tim Pearce, Jong-Hyeon Jeong, Yichen Jia, Jun Zhu |
| 2022 | Certifying Robust Graph Classification under Orthogonal Gromov-Wasserstein Threats. Hongwei Jin, Zishun Yu, Xinhua Zhang |
| 2022 | Certifying Some Distributional Fairness with Subpopulation Decomposition. Mintong Kang, Linyi Li, Maurice Weber, Yang Liu, Ce Zhang, Bo Li |
| 2022 | Chain of Thought Imitation with Procedure Cloning. Mengjiao Yang, Dale Schuurmans, Pieter Abbeel, Ofir Nachum |
| 2022 | Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, Denny Zhou |
| 2022 | Challenging Common Assumptions in Convex Reinforcement Learning. Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli |
| 2022 | Change Event Dataset for Discovery from Spatio-temporal Remote Sensing Imagery. Utkarsh Mall, Bharath Hariharan, Kavita Bala |
| 2022 | Change-point Detection for Sparse and Dense Functional Data in General Dimensions. Carlos Misael Madrid Padilla, Daren Wang, Zifeng Zhao, Yi Yu |
| 2022 | Chaotic Dynamics are Intrinsic to Neural Network Training with SGD. Luis Herrmann, Maximilian Granz, Tim Landgraf |
| 2022 | Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent. Soon Hoe Lim, Yijun Wan, Umut Simsekli |
| 2022 | Characteristics of Harmful Text: Towards Rigorous Benchmarking of Language Models. Maribeth Rauh, John Mellor, Jonathan Uesato, Po-Sen Huang, Johannes Welbl, Laura Weidinger, Sumanth Dathathri, Amelia Glaese, Geoffrey Irving, Iason Gabriel, William Isaac, Lisa Anne Hendricks |
| 2022 | Characterization of Excess Risk for Locally Strongly Convex Population Risk. Mingyang Yi, Ruoyu Wang, Zhi-Ming Ma |
| 2022 | Characterizing Datapoints via Second-Split Forgetting. Pratyush Maini, Saurabh Garg, Zachary C. Lipton, J. Zico Kolter |
| 2022 | Characterizing the Ventral Visual Stream with Response-Optimized Neural Encoding Models. Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, Mert R. Sabuncu |
| 2022 | Chartalist: Labeled Graph Datasets for UTXO and Account-based Blockchains. Kiarash Shamsi, Friedhelm Victor, Murat Kantarcioglu, Yulia R. Gel, Cuneyt Gurcan Akcora |
| 2022 | Chefs' Random Tables: Non-Trigonometric Random Features. Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller |
| 2022 | Chroma-VAE: Mitigating Shortcut Learning with Generative Classifiers. Wanqian Yang, Polina Kirichenko, Micah Goldblum, Andrew Gordon Wilson |
| 2022 | Chromatic Correlation Clustering, Revisited. Qing Xiu, Kai Han, Jing Tang, Shuang Cui, He Huang |
| 2022 | Class-Aware Adversarial Transformers for Medical Image Segmentation. Chenyu You, Ruihan Zhao, Fenglin Liu, Siyuan Dong, Sandeep Chinchali, Ufuk Topcu, Lawrence H. Staib, James S. Duncan |
| 2022 | Class-Dependent Label-Noise Learning with Cycle-Consistency Regularization. De Cheng, Yixiong Ning, Nannan Wang, Xinbo Gao, Heng Yang, Yuxuan Du, Bo Han, Tongliang Liu |
| 2022 | ClimbQ: Class Imbalanced Quantization Enabling Robustness on Efficient Inferences. Ting-An Chen, De-Nian Yang, Ming-Syan Chen |
| 2022 | Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise. Eduard Gorbunov, Marina Danilova, David Dobre, Pavel E. Dvurechenskii, Alexander V. Gasnikov, Gauthier Gidel |
| 2022 | Cluster Randomized Designs for One-Sided Bipartite Experiments. Jennifer Brennan, Vahab Mirrokni, Jean Pouget-Abadie |
| 2022 | Cluster and Aggregate: Face Recognition with Large Probe Set. Minchul Kim, Feng Liu, Anil K. Jain, Xiaoming Liu |
| 2022 | Co-Modality Graph Contrastive Learning for Imbalanced Node Classification. Yiyue Qian, Chunhui Zhang, Yiming Zhang, Qianlong Wen, Yanfang Ye, Chuxu Zhang |
| 2022 | CoNSoLe: Convex Neural Symbolic Learning. Haoran Li, Yang Weng, Hanghang Tong |
| 2022 | CoNT: Contrastive Neural Text Generation. Chenxin An, Jiangtao Feng, Kai Lv, Lingpeng Kong, Xipeng Qiu, Xuanjing Huang |
| 2022 | CoPur: Certifiably Robust Collaborative Inference via Feature Purification. Jing Liu, Chulin Xie, Sanmi Koyejo, Bo Li |
| 2022 | Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone. Zi-Yi Dou, Aishwarya Kamath, Zhe Gan, Pengchuan Zhang, Jianfeng Wang, Linjie Li, Zicheng Liu, Ce Liu, Yann LeCun, Nanyun Peng, Jianfeng Gao, Lijuan Wang |
| 2022 | CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning. Hung Le, Yue Wang, Akhilesh Deepak Gotmare, Silvio Savarese, Steven Chu-Hong Hoi |
| 2022 | Coded Residual Transform for Generalizable Deep Metric Learning. Shichao Kan, Yixiong Liang, Min Li, Yigang Cen, Jianxin Wang, Zhihai He |
| 2022 | CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers. Ming Ding, Wendi Zheng, Wenyi Hong, Jie Tang |
| 2022 | Collaborative Decision Making Using Action Suggestions. Dylan M. Asmar, Mykel J. Kochenderfer |
| 2022 | Collaborative Learning by Detecting Collaboration Partners. Shu Ding, Wei Wang |
| 2022 | Collaborative Learning of Discrete Distributions under Heterogeneity and Communication Constraints. Xinmeng Huang, Donghwan Lee, Edgar Dobriban, Hamed Hassani |
| 2022 | Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds. Aritra Mitra, Arman Adibi, George J. Pappas, Hamed Hassani |
| 2022 | ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs. Limei Wang, Yi Liu, Yuchao Lin, Haoran Liu, Shuiwang Ji |
| 2022 | ComGAN: Unsupervised Disentanglement and Segmentation via Image Composition. Rui Ding, Kehua Guo, Xiangyuan Zhu, Zheng Wu, Liwei Wang |
| 2022 | ComMU: Dataset for Combinatorial Music Generation. Lee Hyun, Taehyun Kim, Hyolim Kang, Minjoo Ki, Hyeonchan Hwang, Kwanho Park, Sharang Han, Seon Joo Kim |
| 2022 | Combinatorial Bandits with Linear Constraints: Beyond Knapsacks and Fairness. Qingsong Liu, Weihang Xu, Siwei Wang, Zhixuan Fang |
| 2022 | Combining Explicit and Implicit Regularization for Efficient Learning in Deep Networks. Dan Zhao |
| 2022 | Communicating Natural Programs to Humans and Machines. Samuel Acquaviva, Yewen Pu, Marta Kryven, Theodoros Sechopoulos, Catherine Wong, Gabrielle E. Ecanow, Maxwell I. Nye, Michael Henry Tessler, Josh Tenenbaum |
| 2022 | Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox. Abdurakhmon Sadiev, Dmitry Kovalev, Peter Richtárik |
| 2022 | Communication Efficient Distributed Learning for Kernelized Contextual Bandits. Chuanhao Li, Huazheng Wang, Mengdi Wang, Hongning Wang |
| 2022 | Communication Efficient Federated Learning for Generalized Linear Bandits. Chuanhao Li, Hongning Wang |
| 2022 | Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate. Zhuoqing Song, Weijian Li, Kexin Jin, Lei Shi, Ming Yan, Wotao Yin, Kun Yuan |
| 2022 | Communication-efficient distributed eigenspace estimation with arbitrary node failures. Vasileios Charisopoulos, Anil Damle |
| 2022 | Composite Feature Selection Using Deep Ensembles. Fergus Imrie, Alexander Norcliffe, Pietro Lió, Mihaela van der Schaar |
| 2022 | Composition Theorems for Interactive Differential Privacy. Xin Lyu |
| 2022 | Compositional Generalization in Unsupervised Compositional Representation Learning: A Study on Disentanglement and Emergent Language. Zhenlin Xu, Marc Niethammer, Colin Raffel |
| 2022 | Compositional generalization through abstract representations in human and artificial neural networks. Takuya Ito, Tim Klinger, Douglas Schultz, John Murray, Michael W. Cole, Mattia Rigotti |
| 2022 | Compressible-composable NeRF via Rank-residual Decomposition. Jiaxiang Tang, Xiaokang Chen, Jingbo Wang, Gang Zeng |
| 2022 | Computationally Efficient Horizon-Free Reinforcement Learning for Linear Mixture MDPs. Dongruo Zhou, Quanquan Gu |
| 2022 | Concentration of Data Encoding in Parameterized Quantum Circuits. Guangxi Li, Ruilin Ye, Xuanqiang Zhao, Xin Wang |
| 2022 | Concept Activation Regions: A Generalized Framework For Concept-Based Explanations. Jonathan Crabbé, Mihaela van der Schaar |
| 2022 | Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off. Mateo Espinosa Zarlenga, Pietro Barbiero, Gabriele Ciravegna, Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Zohreh Shams, Frédéric Precioso, Stefano Melacci, Adrian Weller, Pietro Lió, Mateja Jamnik |
| 2022 | Concrete Score Matching: Generalized Score Matching for Discrete Data. Chenlin Meng, Kristy Choi, Jiaming Song, Stefano Ermon |
| 2022 | Conditional Diffusion Process for Inverse Halftoning. Hao Jiang, Yadong Mu |
| 2022 | Conditional Independence Testing with Heteroskedastic Data and Applications to Causal Discovery. Wiebke Günther, Urmi Ninad, Jonas Wahl, Jakob Runge |
| 2022 | Conditional Meta-Learning of Linear Representations. Giulia Denevi, Massimiliano Pontil, Carlo Ciliberto |
| 2022 | ConfLab: A Data Collection Concept, Dataset, and Benchmark for Machine Analysis of Free-Standing Social Interactions in the Wild. Chirag Raman, José Vargas Quiros, Stephanie Tan, Ashraful Islam, Ekin Gedik, Hayley Hung |
| 2022 | Confidence-based Reliable Learning under Dual Noises. Peng Cui, Yang Yue, Zhijie Deng, Jun Zhu |
| 2022 | Confident Adaptive Language Modeling. Tal Schuster, Adam Fisch, Jai Gupta, Mostafa Dehghani, Dara Bahri, Vinh Tran, Yi Tay, Donald Metzler |
| 2022 | Confident Approximate Policy Iteration for Efficient Local Planning in $q^\pi$-realizable MDPs. Gellért Weisz, András György, Tadashi Kozuno, Csaba Szepesvári |
| 2022 | Conformal Frequency Estimation with Sketched Data. Matteo Sesia, Stefano Favaro |
| 2022 | Conformal Off-Policy Prediction in Contextual Bandits. Muhammad Faaiz Taufiq, Jean-Francois Ton, Rob Cornish, Yee Whye Teh, Arnaud Doucet |
| 2022 | Conformal Prediction with Temporal Quantile Adjustments. Zhen Lin, Shubhendu Trivedi, Jimeng Sun |
| 2022 | Conformalized Fairness via Quantile Regression. Meichen Liu, Lei Ding, Dengdeng Yu, Wulong Liu, Linglong Kong, Bei Jiang |
| 2022 | ConfounderGAN: Protecting Image Data Privacy with Causal Confounder. Qi Tian, Kun Kuang, Kelu Jiang, Furui Liu, Zhihua Wang, Fei Wu |
| 2022 | Conservative Dual Policy Optimization for Efficient Model-Based Reinforcement Learning. Shenao Zhang |
| 2022 | Consistency of Constrained Spectral Clustering under Graph Induced Fair Planted Partitions. Shubham Gupta, Ambedkar Dukkipati |
| 2022 | Consistent Interpolating Ensembles via the Manifold-Hilbert Kernel. Yutong Wang, Clayton Scott |
| 2022 | Consistent Sufficient Explanations and Minimal Local Rules for explaining the decision of any classifier or regressor. Salim I. Amoukou, Nicolas J.-B. Brunel |
| 2022 | Constants of motion network. Muhammad Firmansyah Kasim, Yi Heng Lim |
| 2022 | Constrained GPI for Zero-Shot Transfer in Reinforcement Learning. Jaekyeom Kim, Seohong Park, Gunhee Kim |
| 2022 | Constrained Langevin Algorithms with L-mixing External Random Variables. Yuping Zheng, Andrew G. Lamperski |
| 2022 | Constrained Predictive Coding as a Biologically Plausible Model of the Cortical Hierarchy. Siavash Golkar, Tiberiu Tesileanu, Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii |
| 2022 | Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data. Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi |
| 2022 | Constrained Update Projection Approach to Safe Policy Optimization. Long Yang, Jiaming Ji, Juntao Dai, Linrui Zhang, Binbin Zhou, Pengfei Li, Yaodong Yang, Gang Pan |
| 2022 | Constraining Gaussian Processes to Systems of Linear Ordinary Differential Equations. Andreas Besginow, Markus Lange-Hegermann |
| 2022 | Contact-aware Human Motion Forecasting. Wei Mao, Miaomiao Liu, Richard I. Hartley, Mathieu Salzmann |
| 2022 | Context-Based Dynamic Pricing with Partially Linear Demand Model. Jinzhi Bu, David Simchi-Levi, Chonghuan Wang |
| 2022 | Contextual Bandits with Knapsacks for a Conversion Model. Zhen Li, Gilles Stoltz |
| 2022 | Contextual Dynamic Pricing with Unknown Noise: Explore-then-UCB Strategy and Improved Regrets. Yiyun Luo, Will Wei Sun, Yufeng Liu |
| 2022 | Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification. Massimiliano Patacchiola, John Bronskill, Aliaksandra Shysheya, Katja Hofmann, Sebastian Nowozin, Richard E. Turner |
| 2022 | Continual Learning In Environments With Polynomial Mixing Times. Matthew Riemer, Sharath Chandra Raparthy, Ignacio Cases, Gopeshh Subbaraj, Maximilian Puelma Touzel, Irina Rish |
| 2022 | Continual Learning with Evolving Class Ontologies. Zhiqiu Lin, Deepak Pathak, Yu-Xiong Wang, Deva Ramanan, Shu Kong |
| 2022 | Continual learning: a feature extraction formalization, an efficient algorithm, and fundamental obstructions. Binghui Peng, Andrej Risteski |
| 2022 | Continuous Deep Q-Learning in Optimal Control Problems: Normalized Advantage Functions Analysis. Anton Plaksin, Stepan Martyanov |
| 2022 | Continuous MDP Homomorphisms and Homomorphic Policy Gradient. Sahand Rezaei-Shoshtari, Rosie Zhao, Prakash Panangaden, David Meger, Doina Precup |
| 2022 | Continuously Tempered PDMP samplers. Matthew Sutton, Robert Salomone, Augustin Chevallier, Paul Fearnhead |
| 2022 | Contrastive Adapters for Foundation Model Group Robustness. Michael Zhang, Christopher Ré |
| 2022 | Contrastive Graph Structure Learning via Information Bottleneck for Recommendation. Chunyu Wei, Jian Liang, Di Liu, Fei Wang |
| 2022 | Contrastive Language-Image Pre-Training with Knowledge Graphs. Xuran Pan, Tianzhu Ye, Dongchen Han, Shiji Song, Gao Huang |
| 2022 | Contrastive Learning as Goal-Conditioned Reinforcement Learning. Benjamin Eysenbach, Tianjun Zhang, Sergey Levine, Ruslan Salakhutdinov |
| 2022 | Contrastive Neural Ratio Estimation. Benjamin Kurt Miller, Christoph Weniger, Patrick Forré |
| 2022 | Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods. Randall Balestriero, Yann LeCun |
| 2022 | Controllable 3D Face Synthesis with Conditional Generative Occupancy Fields. Keqiang Sun, Shangzhe Wu, Zhaoyang Huang, Ning Zhang, Quan Wang, Hongsheng Li |
| 2022 | Controllable Text Generation with Neurally-Decomposed Oracle. Tao Meng, Sidi Lu, Nanyun Peng, Kai-Wei Chang |
| 2022 | Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints. Jose Gallego-Posada, Juan Ramirez, Akram Erraqabi, Yoshua Bengio, Simon Lacoste-Julien |
| 2022 | Convergence beyond the over-parameterized regime using Rayleigh quotients. David A. R. Robin, Kevin Scaman, Marc Lelarge |
| 2022 | Convergence for score-based generative modeling with polynomial complexity. Holden Lee, Jianfeng Lu, Yixin Tan |
| 2022 | Convergent Representations of Computer Programs in Human and Artificial Neural Networks. Shashank Srikant, Ben Lipkin, Anna A. Ivanova, Evelina Fedorenko, Una-May O'Reilly |
| 2022 | Convexity Certificates from Hessians. Julien Klaus, Niklas Merk, Konstantin Wiedom, Sören Laue, Joachim Giesen |
| 2022 | Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited. Mingguo He, Zhewei Wei, Ji-Rong Wen |
| 2022 | Cooperative Distribution Alignment via JSD Upper Bound. Wonwoong Cho, Ziyu Gong, David I. Inouye |
| 2022 | Coordinate Linear Variance Reduction for Generalized Linear Programming. Chaobing Song, Cheuk Yin Lin, Stephen J. Wright, Jelena Diakonikolas |
| 2022 | Coordinates Are NOT Lonely - Codebook Prior Helps Implicit Neural 3D representations. Fukun Yin, Wen Liu, Zilong Huang, Pei Cheng, Tao Chen, Gang Yu |
| 2022 | Coreset for Line-Sets Clustering. Sagi Lotan, Ernesto Evgeniy Sanches Shayda, Dan Feldman |
| 2022 | Coresets for Relational Data and The Applications. Jiaxiang Chen, Qingyuan Yang, Ruomin Huang, Hu Ding |
| 2022 | Coresets for Vertical Federated Learning: Regularized Linear Regression and $K$-Means Clustering. Lingxiao Huang, Zhize Li, Jialin Sun, Haoyu Zhao |
| 2022 | Coresets for Wasserstein Distributionally Robust Optimization Problems. Ruomin Huang, Jiawei Huang, Wenjie Liu, Hu Ding |
| 2022 | Cost-Sensitive Self-Training for Optimizing Non-Decomposable Metrics. Harsh Rangwani, Shrinivas Ramasubramanian, Sho Takemori, Kato Takashi, Yuhei Umeda, Venkatesh Babu R. |
| 2022 | Cost-efficient Gaussian tensor network embeddings for tensor-structured inputs. Linjian Ma, Edgar Solomonik |
| 2022 | Could Giant Pre-trained Image Models Extract Universal Representations? Yutong Lin, Ze Liu, Zheng Zhang, Han Hu, Nanning Zheng, Stephen Lin, Yue Cao |
| 2022 | Counterfactual Fairness with Partially Known Causal Graph. Aoqi Zuo, Susan Wei, Tongliang Liu, Bo Han, Kun Zhang, Mingming Gong |
| 2022 | Counterfactual Neural Temporal Point Process for Estimating Causal Influence of Misinformation on Social Media. Yizhou Zhang, Defu Cao, Yan Liu |
| 2022 | Counterfactual Temporal Point Processes. Kimia Noorbakhsh, Manuel Gomez-Rodriguez |
| 2022 | Counterfactual harm. Jonathan G. Richens, Rory Beard, Daniel H. Thompson |
| 2022 | CoupAlign: Coupling Word-Pixel with Sentence-Mask Alignments for Referring Image Segmentation. Zicheng Zhang, Yi Zhu, Jianzhuang Liu, Xiaodan Liang, Wei Ke |
| 2022 | CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View Completion. Philippe Weinzaepfel, Vincent Leroy, Thomas Lucas, Romain Brégier, Yohann Cabon, Vaibhav Arora, Leonid Antsfeld, Boris Chidlovskii, Gabriela Csurka, Jérôme Revaud |
| 2022 | Cross Aggregation Transformer for Image Restoration. Zheng Chen, Yulun Zhang, Jinjin Gu, Yongbing Zhang, Linghe Kong, Xin Yuan |
| 2022 | Cross-Image Context for Single Image Inpainting. Tingliang Feng, Wei Feng, Weiqi Li, Di Lin |
| 2022 | Cross-Linked Unified Embedding for cross-modality representation learning. Xinming Tu, Zhi-Jie Cao, Chenrui Xia, Sara Mostafavi, Ge Gao |
| 2022 | Cross-modal Learning for Image-Guided Point Cloud Shape Completion. Emanuele Aiello, Diego Valsesia, Enrico Magli |
| 2022 | CryptoGCN: Fast and Scalable Homomorphically Encrypted Graph Convolutional Network Inference. Ran Ran, Wei Wang, Quan Gang, Jieming Yin, Nuo Xu, Wujie Wen |
| 2022 | Cryptographic Hardness of Learning Halfspaces with Massart Noise. Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren |
| 2022 | Curious Exploration via Structured World Models Yields Zero-Shot Object Manipulation. Cansu Sancaktar, Sebastian Blaes, Georg Martius |
| 2022 | Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation. Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Fei Fang, Ding Zhao |
| 2022 | CyCLIP: Cyclic Contrastive Language-Image Pretraining. Shashank Goel, Hritik Bansal, Sumit Bhatia, Ryan A. Rossi, Vishwa Vinay, Aditya Grover |
| 2022 | DABS 2.0: Improved Datasets and Algorithms for Universal Self-Supervision. Alex Tamkin, Gaurab Banerjee, Mohamed Owda, Vincent Liu, Shashank Rammoorthy, Noah D. Goodman |
| 2022 | DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization. Kevin Bello, Bryon Aragam, Pradeep Ravikumar |
| 2022 | DARE: Disentanglement-Augmented Rationale Extraction. Linan Yue, Qi Liu, Yichao Du, Yanqing An, Li Wang, Enhong Chen |
| 2022 | DART: Articulated Hand Model with Diverse Accessories and Rich Textures. Daiheng Gao, Yuliang Xiu, Kailin Li, Lixin Yang, Feng Wang, Peng Zhang, Bang Zhang, Cewu Lu, Ping Tan |
| 2022 | DASCO: Dual-Generator Adversarial Support Constrained Offline Reinforcement Learning. Quan Vuong, Aviral Kumar, Sergey Levine, Yevgen Chebotar |
| 2022 | DC-BENCH: Dataset Condensation Benchmark. Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh |
| 2022 | DDXPlus: A New Dataset For Automatic Medical Diagnosis. Arsène Fansi Tchango, Rishab Goel, Zhi Wen, Julien Martel, Joumana Ghosn |
| 2022 | DENSE: Data-Free One-Shot Federated Learning. Jie Zhang, Chen Chen, Bo Li, Lingjuan Lyu, Shuang Wu, Shouhong Ding, Chunhua Shen, Chao Wu |
| 2022 | DGD^2: A Linearly Convergent Distributed Algorithm For High-dimensional Statistical Recovery. Marie Maros, Gesualdo Scutari |
| 2022 | DGraph: A Large-Scale Financial Dataset for Graph Anomaly Detection. Xuanwen Huang, Yang Yang, Yang Wang, Chunping Wang, Zhisheng Zhang, Jiarong Xu, Lei Chen, Michalis Vazirgiannis |
| 2022 | DHRL: A Graph-Based Approach for Long-Horizon and Sparse Hierarchical Reinforcement Learning. Seungjae Lee, Jigang Kim, Inkyu Jang, H. Jin Kim |
| 2022 | DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems. Ruizhong Qiu, Zhiqing Sun, Yiming Yang |
| 2022 | DISCO: Adversarial Defense with Local Implicit Functions. Chih-Hui Ho, Nuno Vasconcelos |
| 2022 | DMAP: a Distributed Morphological Attention Policy for learning to locomote with a changing body. Alberto Silvio Chiappa, Alessandro Marin Vargas, Alexander Mathis |
| 2022 | DNA: Proximal Policy Optimization with a Dual Network Architecture. Matthew Aitchison, Penny Sweetser |
| 2022 | DOMINO: Decomposed Mutual Information Optimization for Generalized Context in Meta-Reinforcement Learning. Yao Mu, Yuzheng Zhuang, Fei Ni, Bin Wang, Jianyu Chen, Jianye Hao, Ping Luo |
| 2022 | DOPE: Doubly Optimistic and Pessimistic Exploration for Safe Reinforcement Learning. Archana Bura, Aria HasanzadeZonuzy, Dileep Kalathil, Srinivas Shakkottai, Jean-François Chamberland |
| 2022 | DP-PCA: Statistically Optimal and Differentially Private PCA. Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh |
| 2022 | DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps. Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu |
| 2022 | DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing. Jiawei Shao, Yuchang Sun, Songze Li, Jun Zhang |
| 2022 | DTG-SSOD: Dense Teacher Guidance for Semi-Supervised Object Detection. Gang Li, Xiang Li, Yujie Wang, Yichao Wu, Ding Liang, Shanshan Zhang |
| 2022 | D^2NeRF: Self-Supervised Decoupling of Dynamic and Static Objects from a Monocular Video. Tianhao Wu, Fangcheng Zhong, Andrea Tagliasacchi, Forrester Cole, Cengiz Öztireli |
| 2022 | DaDA: Distortion-aware Domain Adaptation for Unsupervised Semantic Segmentation. Sujin Jang, Joohan Na, Dokwan Oh |
| 2022 | Dance of SNN and ANN: Solving binding problem by combining spike timing and reconstructive attention. Hao Zheng, Hui Lin, Rong Zhao, Luping Shi |
| 2022 | Data Augmentation MCMC for Bayesian Inference from Privatized Data. Nianqiao Ju, Jordan Awan, Ruobin Gong, Vinayak Rao |
| 2022 | Data Augmentation for Compositional Data: Advancing Predictive Models of the Microbiome. Elliott Gordon-Rodríguez, Thomas P. Quinn, John P. Cunningham |
| 2022 | Data Distributional Properties Drive Emergent In-Context Learning in Transformers. Stephanie C. Y. Chan, Adam Santoro, Andrew K. Lampinen, Jane X. Wang, Aaditya K. Singh, Pierre H. Richemond, James L. McClelland, Felix Hill |
| 2022 | Data augmentation for efficient learning from parametric experts. Alexandre Galashov, Joshua Scott Merel, Nicolas Heess |
| 2022 | Data-Driven Conditional Robust Optimization. Abhilash Reddy Chenreddy, Nymisha Bandi, Erick Delage |
| 2022 | Data-Driven Offline Decision-Making via Invariant Representation Learning. Han Qi, Yi Su, Aviral Kumar, Sergey Levine |
| 2022 | Data-Efficient Augmentation for Training Neural Networks. Tian Yu Liu, Baharan Mirzasoleiman |
| 2022 | Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data. Allen Nie, Yannis Flet-Berliac, Deon R. Jordan, William Steenbergen, Emma Brunskill |
| 2022 | Data-Efficient Structured Pruning via Submodular Optimization. Marwa El Halabi, Suraj Srinivas, Simon Lacoste-Julien |
| 2022 | Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data. Nabeel Seedat, Jonathan Crabbé, Ioana Bica, Mihaela van der Schaar |
| 2022 | DataMUX: Data Multiplexing for Neural Networks. Vishvak Murahari, Carlos E. Jimenez, Runzhe Yang, Karthik Narasimhan |
| 2022 | Dataset Distillation using Neural Feature Regression. Yongchao Zhou, Ehsan Nezhadarya, Jimmy Ba |
| 2022 | Dataset Distillation via Factorization. Songhua Liu, Kai Wang, Xingyi Yang, Jingwen Ye, Xinchao Wang |
| 2022 | Dataset Inference for Self-Supervised Models. Adam Dziedzic, Haonan Duan, Muhammad Ahmad Kaleem, Nikita Dhawan, Jonas Guan, Yannis Cattan, Franziska Boenisch, Nicolas Papernot |
| 2022 | DeVRF: Fast Deformable Voxel Radiance Fields for Dynamic Scenes. Jiawei Liu, Yan-Pei Cao, Weijia Mao, Wenqiao Zhang, David Junhao Zhang, Jussi Keppo, Ying Shan, Xiaohu Qie, Mike Zheng Shou |
| 2022 | Debiased Causal Tree: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding. Caizhi Tang, Huiyuan Wang, Xinyu Li, Qing Cui, Ya-Lin Zhang, Feng Zhu, Longfei Li, Jun Zhou, Linbo Jiang |
| 2022 | Debiased Machine Learning without Sample-Splitting for Stable Estimators. Qizhao Chen, Vasilis Syrgkanis, Morgane Austern |
| 2022 | Debiased Self-Training for Semi-Supervised Learning. Baixu Chen, Junguang Jiang, Ximei Wang, Pengfei Wan, Jianmin Wang, Mingsheng Long |
| 2022 | Debiased, Longitudinal and Coordinated Drug Recommendation through Multi-Visit Clinic Records. Hongda Sun, Shufang Xie, Shuqi Li, Yuhan Chen, Ji-Rong Wen, Rui Yan |
| 2022 | Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure. Shaohua Fan, Xiao Wang, Yanhu Mo, Chuan Shi, Jian Tang |
| 2022 | Debugging and Explaining Metric Learning Approaches: An Influence Function Based Perspective. Ruofan Liu, Yun Lin, Xianglin Yang, Jin Song Dong |
| 2022 | Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks. Shuoguang Yang, Xuezhou Zhang, Mengdi Wang |
| 2022 | Decentralized Local Stochastic Extra-Gradient for Variational Inequalities. Aleksandr Beznosikov, Pavel E. Dvurechensky, Anastasia Koloskova, Valentin Samokhin, Sebastian U. Stich, Alexander V. Gasnikov |
| 2022 | Decentralized Training of Foundation Models in Heterogeneous Environments. Binhang Yuan, Yongjun He, Jared Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Ré, Ce Zhang |
| 2022 | Decentralized, Communication- and Coordination-free Learning in Structured Matching Markets. Chinmay Maheshwari, Shankar Sastry, Eric Mazumdar |
| 2022 | Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning. Dilip Arumugam, Benjamin Van Roy |
| 2022 | Decision Trees with Short Explainable Rules. Victor Feitosa Souza, Ferdinando Cicalese, Eduardo Sany Laber, Marco Molinaro |
| 2022 | Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision Losses. Sanket Shah, Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe |
| 2022 | Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal. Yucheng Shi, Yahong Han, Yu-an Tan, Xiaohui Kuang |
| 2022 | Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient Oracle Complexity. Sally Dong, Haotian Jiang, Yin Tat Lee, Swati Padmanabhan, Guanghao Ye |
| 2022 | Decomposed Knowledge Distillation for Class-Incremental Semantic Segmentation. Donghyeon Baek, Youngmin Oh, Sanghoon Lee, Junghyup Lee, Bumsub Ham |
| 2022 | Decomposing NeRF for Editing via Feature Field Distillation. Sosuke Kobayashi, Eiichi Matsumoto, Vincent Sitzmann |
| 2022 | Deconfounded Representation Similarity for Comparison of Neural Networks. Tianyu Cui, Yogesh Kumar, Pekka Marttinen, Samuel Kaski |
| 2022 | Decoupled Context Processing for Context Augmented Language Modeling. Zonglin Li, Ruiqi Guo, Sanjiv Kumar |
| 2022 | Decoupled Self-supervised Learning for Graphs. Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang |
| 2022 | Decoupling Classifier for Boosting Few-shot Object Detection and Instance Segmentation. Bin-Bin Gao, Xiaochen Chen, Zhongyi Huang, Congchong Nie, Jun Liu, Jinxiang Lai, Guannan Jiang, Xi Wang, Chengjie Wang |
| 2022 | Decoupling Features in Hierarchical Propagation for Video Object Segmentation. Zongxin Yang, Yi Yang |
| 2022 | Decoupling Knowledge from Memorization: Retrieval-augmented Prompt Learning. Xiang Chen, Lei Li, Ningyu Zhang, Xiaozhuan Liang, Shumin Deng, Chuanqi Tan, Fei Huang, Luo Si, Huajun Chen |
| 2022 | Deep Active Learning by Leveraging Training Dynamics. Haonan Wang, Wei Huang, Ziwei Wu, Hanghang Tong, Andrew Margenot, Jingrui He |
| 2022 | Deep Architecture Connectivity Matters for Its Convergence: A Fine-Grained Analysis. Wuyang Chen, Wei Huang, Xinyu Gong, Boris Hanin, Zhangyang Wang |
| 2022 | Deep Attentive Belief Propagation: Integrating Reasoning and Learning for Solving Constraint Optimization Problems. Yanchen Deng, Shufeng Kong, Caihua Liu, Bo An |
| 2022 | Deep Bidirectional Language-Knowledge Graph Pretraining. Michihiro Yasunaga, Antoine Bosselut, Hongyu Ren, Xikun Zhang, Christopher D. Manning, Percy Liang, Jure Leskovec |
| 2022 | Deep Combinatorial Aggregation. Yuesong Shen, Daniel Cremers |
| 2022 | Deep Compression of Pre-trained Transformer Models. Naigang Wang, Chi-Chun (Charlie) Liu, Swagath Venkataramani, Sanchari Sen, Chia-Yu Chen, Kaoutar El Maghraoui, Vijayalakshmi Srinivasan, Leland Chang |
| 2022 | Deep Counterfactual Estimation with Categorical Background Variables. Edward De Brouwer |
| 2022 | Deep Differentiable Logic Gate Networks. Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen |
| 2022 | Deep Ensembles Work, But Are They Necessary? Taiga Abe, Estefany Kelly Buchanan, Geoff Pleiss, Richard S. Zemel, John P. Cunningham |
| 2022 | Deep Equilibrium Approaches to Diffusion Models. Ashwini Pokle, Zhengyang Geng, J. Zico Kolter |
| 2022 | Deep Fourier Up-Sampling. Man Zhou, Hu Yu, Jie Huang, Feng Zhao, Jinwei Gu, Chen Change Loy, Deyu Meng, Chongyi Li |
| 2022 | Deep Generalized Schrödinger Bridge. Guan-Horng Liu, Tianrong Chen, Oswin So, Evangelos A. Theodorou |
| 2022 | Deep Generative Model for Periodic Graphs. Shiyu Wang, Xiaojie Guo, Liang Zhao |
| 2022 | Deep Hierarchical Planning from Pixels. Danijar Hafner, Kuang-Huei Lee, Ian Fischer, Pieter Abbeel |
| 2022 | Deep Learning Methods for Proximal Inference via Maximum Moment Restriction. Benjamin Kompa, David R. Bellamy, Thomas Kolokotrones, James M. Robins, Andrew Beam |
| 2022 | Deep Model Reassembly. Xingyi Yang, Daquan Zhou, Songhua Liu, Jingwen Ye, Xinchao Wang |
| 2022 | Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies. Shachi Deshpande, Kaiwen Wang, Dhruv Sreenivas, Zheng Li, Volodymyr Kuleshov |
| 2022 | Deep Surrogate Assisted Generation of Environments. Varun Bhatt, Bryon Tjanaka, Matthew C. Fontaine, Stefanos Nikolaidis |
| 2022 | Deep invariant networks with differentiable augmentation layers. Cédric Rommel, Thomas Moreau, Alexandre Gramfort |
| 2022 | DeepFoids: Adaptive Bio-Inspired Fish Simulation with Deep Reinforcement Learning. Yuko Ishiwaka, Xiao S. Zeng, Shun Ogawa, Donovan Westwater, Tadayuki Tone, Masaki Nakada |
| 2022 | DeepInteraction: 3D Object Detection via Modality Interaction. Zeyu Yang, Jiaqi Chen, Zhenwei Miao, Wei Li, Xiatian Zhu, Li Zhang |
| 2022 | DeepMed: Semiparametric Causal Mediation Analysis with Debiased Deep Learning. Siqi Xu, Lin Liu, Zhonghua Liu |
| 2022 | DeepTOP: Deep Threshold-Optimal Policy for MDPs and RMABs. Khaled Nakhleh, I-Hong Hou |
| 2022 | Defending Against Adversarial Attacks via Neural Dynamic System. Xiyuan Li, Xin Zou, Weiwei Liu |
| 2022 | Defining and Characterizing Reward Gaming. Joar Skalse, Nikolaus H. R. Howe, Dmitrii Krasheninnikov, David Krueger |
| 2022 | Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imaging. Yuanhao Cai, Jing Lin, Haoqian Wang, Xin Yuan, Henghui Ding, Yulun Zhang, Radu Timofte, Luc Van Gool |
| 2022 | Deliberated Domain Bridging for Domain Adaptive Semantic Segmentation. Lin Chen, Zhixiang Wei, Xin Jin, Huaian Chen, Miao Zheng, Kai Chen, Yi Jin |
| 2022 | Delving into Out-of-Distribution Detection with Vision-Language Representations. Yifei Ming, Ziyang Cai, Jiuxiang Gu, Yiyou Sun, Wei Li, Yixuan Li |
| 2022 | Delving into Sequential Patches for Deepfake Detection. Jiazhi Guan, Hang Zhou, Zhibin Hong, Errui Ding, Jingdong Wang, Chengbin Quan, Youjian Zhao |
| 2022 | Denoising Diffusion Restoration Models. Bahjat Kawar, Michael Elad, Stefano Ermon, Jiaming Song |
| 2022 | Dense Interspecies Face Embedding. Sejong Yang, Subin Jeon, Seonghyeon Nam, Seon Joo Kim |
| 2022 | Density-driven Regularization for Out-of-distribution Detection. Wenjian Huang, Hao Wang, Jiahao Xia, Chengyan Wang, Jianguo Zhang |
| 2022 | Depth is More Powerful than Width with Prediction Concatenation in Deep Forest. Shen-Huan Lyu, Yi-Xiao He, Zhi-Hua Zhou |
| 2022 | Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks. Hongjoon Ahn, Yongyi Yang, Quan Gan, Taesup Moon, David P. Wipf |
| 2022 | DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection. Lewei Yao, Jianhua Han, Youpeng Wen, Xiaodan Liang, Dan Xu, Wei Zhang, Zhenguo Li, Chunjing Xu, Hang Xu |
| 2022 | Detecting Abrupt Changes in Sequential Pairwise Comparison Data. Wanshan Li, Alessandro Rinaldo, Daren Wang |
| 2022 | Detection and Localization of Changes in Conditional Distributions. Lizhen Nie, Dan Nicolae |
| 2022 | Deterministic Langevin Monte Carlo with Normalizing Flows for Bayesian Inference. Richard D. P. Grumitt, Biwei Dai, Uros Seljak |
| 2022 | DevFly: Bio-Inspired Development of Binary Connections for Locality Preserving Sparse Codes. Tianqi Wei, Rana Alkhoury Maroun, Qinghai Guo, Barbara Webb |
| 2022 | DiSC: Differential Spectral Clustering of Features. Ram Dyuthi Sristi, Gal Mishne, Ariel Jaffe |
| 2022 | Diagnosing failures of fairness transfer across distribution shift in real-world medical settings. Jessica Schrouff, Natalie Harris, Sanmi Koyejo, Ibrahim M. Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour |
| 2022 | Diagonal State Spaces are as Effective as Structured State Spaces. Ankit Gupta, Albert Gu, Jonathan Berant |
| 2022 | Dict-TTS: Learning to Pronounce with Prior Dictionary Knowledge for Text-to-Speech. Ziyue Jiang, Su Zhe, Zhou Zhao, Qian Yang, Yi Ren, Jinglin Liu, Zhenhui Ye |
| 2022 | Differentiable Analog Quantum Computing for Optimization and Control. Jiaqi Leng, Yuxiang Peng, Yi-Ling Qiao, Ming C. Lin, Xiaodi Wu |
| 2022 | Differentiable hierarchical and surrogate gradient search for spiking neural networks. Kaiwei Che, Luziwei Leng, Kaixuan Zhang, Jianguo Zhang, Qinghu Meng, Jie Cheng, Qinghai Guo, Jianxing Liao |
| 2022 | Differentially Private Covariance Revisited. Wei Dong, Yuting Liang, Ke Yi |
| 2022 | Differentially Private Generalized Linear Models Revisited. Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart, Enayat Ullah |
| 2022 | Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank. Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong |
| 2022 | Differentially Private Learning Needs Hidden State (Or Much Faster Convergence). Jiayuan Ye, Reza Shokri |
| 2022 | Differentially Private Learning with Margin Guarantees. Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh |
| 2022 | Differentially Private Linear Sketches: Efficient Implementations and Applications. Fuheng Zhao, Dan Qiao, Rachel Redberg, Divyakant Agrawal, Amr El Abbadi, Yu-Xiang Wang |
| 2022 | Differentially Private Model Compression. Fatemehsadat Mireshghallah, Arturs Backurs, Huseyin A. Inan, Lukas Wutschitz, Janardhan Kulkarni |
| 2022 | Differentially Private Online-to-batch for Smooth Losses. Qinzi Zhang, Hoang Tran, Ashok Cutkosky |
| 2022 | Diffusion Curvature for Estimating Local Curvature in High Dimensional Data. Dhananjay Bhaskar, Kincaid MacDonald, Oluwadamilola Fasina, Dawson Thomas, Bastian Rieck, Ian Adelstein, Smita Krishnaswamy |
| 2022 | Diffusion Models as Plug-and-Play Priors. Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, Dimitris Samaras |
| 2022 | Diffusion Visual Counterfactual Explanations. Maximilian Augustin, Valentyn Boreiko, Francesco Croce, Matthias Hein |
| 2022 | Diffusion-LM Improves Controllable Text Generation. Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B. Hashimoto |
| 2022 | Diffusion-based Molecule Generation with Informative Prior Bridges. Lemeng Wu, Chengyue Gong, Xingchao Liu, Mao Ye, Qiang Liu |
| 2022 | DigGAN: Discriminator gradIent Gap Regularization for GAN Training with Limited Data. Tiantian Fang, Ruoyu Sun, Alexander G. Schwing |
| 2022 | Direct Advantage Estimation. Hsiao-Ru Pan, Nico Gürtler, Alexander Neitz, Bernhard Schölkopf |
| 2022 | Discovered Policy Optimisation. Chris Lu, Jakub Grudzien Kuba, Alistair Letcher, Luke Metz, Christian Schröder de Witt, Jakob N. Foerster |
| 2022 | Discovering Design Concepts for CAD Sketches. Yuezhi Yang, Hao Pan |
| 2022 | Discovering and Overcoming Limitations of Noise-engineered Data-free Knowledge Distillation. Piyush Raikwar, Deepak Mishra |
| 2022 | Discovery of Single Independent Latent Variable. Uri Shaham, Jonathan Svirsky, Ori Katz, Ronen Talmon |
| 2022 | Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning. Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes |
| 2022 | Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions. Shinsaku Sakaue, Taihei Oki |
| 2022 | Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders. Olivier Jeunen, Ciarán M. Gilligan-Lee, Rishabh Mehrotra, Mounia Lalmas |
| 2022 | Disentangling Transfer in Continual Reinforcement Learning. Maciej Wolczyk, Michal Zajac, Razvan Pascanu, Lukasz Kucinski, Piotr Milos |
| 2022 | Disentangling the Predictive Variance of Deep Ensembles through the Neural Tangent Kernel. Seijin Kobayashi, Pau Vilimelis Aceituno, Johannes von Oswald |
| 2022 | Distilled Gradient Aggregation: Purify Features for Input Attribution in the Deep Neural Network. Giyoung Jeon, Haedong Jeong, Jaesik Choi |
| 2022 | Distilling Representations from GAN Generator via Squeeze and Span. Yu Yang, Xiaotian Cheng, Chang Liu, Hakan Bilen, Xiangyang Ji |
| 2022 | Distinguishing Learning Rules with Brain Machine Interfaces. Jacob P. Portes, Christian Schmid, James M. Murray |
| 2022 | Distinguishing discrete and continuous behavioral variability using warped autoregressive HMMs. Julia Costacurta, Lea Duncker, Blue Sheffer, Winthrop Gillis, Caleb Weinreb, Jeffrey E. Markowitz, Sandeep R. Datta, Alex H. Williams, Scott W. Linderman |
| 2022 | Distributed Distributionally Robust Optimization with Non-Convex Objectives. Yang Jiao, Kai Yang, Dongjin Song |
| 2022 | Distributed Influence-Augmented Local Simulators for Parallel MARL in Large Networked Systems. Miguel Suau, Jinke He, Mustafa Mert Çelikok, Matthijs T. J. Spaan, Frans A. Oliehoek |
| 2022 | Distributed Inverse Constrained Reinforcement Learning for Multi-agent Systems. Shicheng Liu, Minghui Zhu |
| 2022 | Distributed Learning of Conditional Quantiles in the Reproducing Kernel Hilbert Space. Heng Lian |
| 2022 | Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees. Aleksandr Beznosikov, Peter Richtárik, Michael Diskin, Max Ryabinin, Alexander V. Gasnikov |
| 2022 | Distributed Online Convex Optimization with Compressed Communication. Zhipeng Tu, Xi Wang, Yiguang Hong, Lei Wang, Deming Yuan, Guodong Shi |
| 2022 | Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity. Bingqing Song, Ioannis C. Tsaknakis, Chung-Yiu Yau, Hoi-To Wai, Mingyi Hong |
| 2022 | Distribution-Informed Neural Networks for Domain Adaptation Regression. Jun Wu, Jingrui He, Sheng Wang, Kaiyu Guan, Elizabeth A. Ainsworth |
| 2022 | Distributional Convergence of the Sliced Wasserstein Process. Jiaqi Xi, Jonathan Niles-Weed |
| 2022 | Distributional Reinforcement Learning for Risk-Sensitive Policies. Shiau Hong Lim, Ilyas Malik |
| 2022 | Distributional Reward Estimation for Effective Multi-agent Deep Reinforcement Learning. Jifeng Hu, Yanchao Sun, Hechang Chen, Sili Huang, Haiyin Piao, Yi Chang, Lichao Sun |
| 2022 | Distributionally Adaptive Meta Reinforcement Learning. Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal |
| 2022 | Distributionally Robust Optimization via Ball Oracle Acceleration. Yair Carmon, Danielle Hausler |
| 2022 | Distributionally Robust Optimization with Data Geometry. Jiashuo Liu, Jiayun Wu, Bo Li, Peng Cui |
| 2022 | Distributionally robust weighted k-nearest neighbors. Shixiang Zhu, Liyan Xie, Minghe Zhang, Rui Gao, Yao Xie |
| 2022 | DivBO: Diversity-aware CASH for Ensemble Learning. Yu Shen, Yupeng Lu, Yang Li, Yaofeng Tu, Wentao Zhang, Bin Cui |
| 2022 | Diverse Weight Averaging for Out-of-Distribution Generalization. Alexandre Ramé, Matthieu Kirchmeyer, Thibaud Rahier, Alain Rakotomamonjy, Patrick Gallinari, Matthieu Cord |
| 2022 | Diversified Recommendations for Agents with Adaptive Preferences. William Brown, Arpit Agarwal |
| 2022 | Diversity vs. Recognizability: Human-like generalization in one-shot generative models. Victor Boutin, Lakshya Singhal, Xavier Thomas, Thomas Serre |
| 2022 | Divert More Attention to Vision-Language Tracking. Mingzhe Guo, Zhipeng Zhang, Heng Fan, Liping Jing |
| 2022 | Divide and Contrast: Source-free Domain Adaptation via Adaptive Contrastive Learning. Ziyi Zhang, Weikai Chen, Hui Cheng, Zhen Li, Siyuan Li, Liang Lin, Guanbin Li |
| 2022 | Do Current Multi-Task Optimization Methods in Deep Learning Even Help? Derrick Xin, Behrooz Ghorbani, Justin Gilmer, Ankush Garg, Orhan Firat |
| 2022 | Do Residual Neural Networks discretize Neural Ordinary Differential Equations? Michael E. Sander, Pierre Ablin, Gabriel Peyré |
| 2022 | Does GNN Pretraining Help Molecular Representation? Ruoxi Sun, Hanjun Dai, Adams Wei Yu |
| 2022 | Does Momentum Change the Implicit Regularization on Separable Data? Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu |
| 2022 | Does Self-supervised Learning Really Improve Reinforcement Learning from Pixels? Xiang Li, Jinghuan Shang, Srijan Das, Michael S. Ryoo |
| 2022 | Domain Adaptation meets Individual Fairness. And they get along. Debarghya Mukherjee, Felix Petersen, Mikhail Yurochkin, Yuekai Sun |
| 2022 | Domain Adaptation under Open Set Label Shift. Saurabh Garg, Sivaraman Balakrishnan, Zachary C. Lipton |
| 2022 | Domain Generalization by Learning and Removing Domain-specific Features. Yu Ding, Lei Wang, Bin Liang, Shuming Liang, Yang Wang, Fang Chen |
| 2022 | Domain Generalization without Excess Empirical Risk. Ozan Sener, Vladlen Koltun |
| 2022 | Don't Pour Cereal into Coffee: Differentiable Temporal Logic for Temporal Action Segmentation. Ziwei Xu, Yogesh S. Rawat, Yongkang Wong, Mohan S. Kankanhalli, Mubarak Shah |
| 2022 | Don't Roll the Dice, Ask Twice: The Two-Query Distortion of Matching Problems and Beyond. Georgios Amanatidis, Georgios Birmpas, Aris Filos-Ratsikas, Alexandros A. Voudouris |
| 2022 | Double Bubble, Toil and Trouble: Enhancing Certified Robustness through Transitivity. Andrew C. Cullen, Paul Montague, Shijie Liu, Sarah M. Erfani, Benjamin I. P. Rubinstein |
| 2022 | Double Check Your State Before Trusting It: Confidence-Aware Bidirectional Offline Model-Based Imagination. Jiafei Lyu, Xiu Li, Zongqing Lu |
| 2022 | Doubly Robust Counterfactual Classification. Kwangho Kim, Edward H. Kennedy, José R. Zubizarreta |
| 2022 | Doubly-Asynchronous Value Iteration: Making Value Iteration Asynchronous in Actions. Tian Tian, Kenny Young, Richard S. Sutton |
| 2022 | Draft-and-Revise: Effective Image Generation with Contextual RQ-Transformer. Doyup Lee, Chiheon Kim, Saehoon Kim, Minsu Cho, Wook-Shin Han |
| 2022 | Drawing out of Distribution with Neuro-Symbolic Generative Models. Yichao Liang, Josh Tenenbaum, Tuan Anh Le, N. Siddharth |
| 2022 | DreamShard: Generalizable Embedding Table Placement for Recommender Systems. Daochen Zha, Louis Feng, Qiaoyu Tan, Zirui Liu, Kwei-Herng Lai, Bhargav Bhushanam, Yuandong Tian, Arun Kejariwal, Xia Hu |
| 2022 | DropCov: A Simple yet Effective Method for Improving Deep Architectures. Qilong Wang, Mingze Gao, Zhaolin Zhang, Jiangtao Xie, Peihua Li, Qinghua Hu |
| 2022 | Dual-Curriculum Contrastive Multi-Instance Learning for Cancer Prognosis Analysis with Whole Slide Images. Chao Tu, Yu Zhang, Zhenyuan Ning |
| 2022 | Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection. Ge Zhang, Zhenyu Yang, Jia Wu, Jian Yang, Shan Xue, Hao Peng, Jianlin Su, Chuan Zhou, Quan Z. Sheng, Leman Akoglu, Charu C. Aggarwal |
| 2022 | DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations. Ximeng Sun, Ping Hu, Kate Saenko |
| 2022 | Dungeons and Data: A Large-Scale NetHack Dataset. Eric Hambro, Roberta Raileanu, Danielle Rothermel, Vegard Mella, Tim Rocktäschel, Heinrich Küttler, Naila Murray |
| 2022 | Dynamic Fair Division with Partial Information. Gerdus Benadè, Daniel Halpern, Alexandros Psomas |
| 2022 | Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift. Zeyang Zhang, Xin Wang, Ziwei Zhang, Haoyang Li, Zhou Qin, Wenwu Zhu |
| 2022 | Dynamic Inverse Reinforcement Learning for Characterizing Animal Behavior. Zoe Ashwood, Aditi Jha, Jonathan W. Pillow |
| 2022 | Dynamic Learning in Large Matching Markets. Anand Kalvit, Assaf Zeevi |
| 2022 | Dynamic Pricing with Monotonicity Constraint under Unknown Parametric Demand Model. Su Jia, Andrew A. Li, R. Ravi |
| 2022 | Dynamic Sparse Network for Time Series Classification: Learning What to "See". Qiao Xiao, Boqian Wu, Yu Zhang, Shiwei Liu, Mykola Pechenizkiy, Elena Mocanu, Decebal Constantin Mocanu |
| 2022 | Dynamic Tensor Product Regression. Aravind Reddy, Zhao Song, Lichen Zhang |
| 2022 | Dynamic pricing and assortment under a contextual MNL demand. Noémie Périvier, Vineet Goyal |
| 2022 | Dynamics of SGD with Stochastic Polyak Stepsizes: Truly Adaptive Variants and Convergence to Exact Solution. Antonio Orvieto, Simon Lacoste-Julien, Nicolas Loizou |
| 2022 | E-MAPP: Efficient Multi-Agent Reinforcement Learning with Parallel Program Guidance. Can Chang, Ni Mu, Jiajun Wu, Ling Pan, Huazhe Xu |
| 2022 | EAGER: Asking and Answering Questions for Automatic Reward Shaping in Language-guided RL. Thomas Carta, Pierre-Yves Oudeyer, Olivier Sigaud, Sylvain Lamprier |
| 2022 | EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization. Laurent Condat, Kai Yi, Peter Richtárik |
| 2022 | EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations. Min Zhao, Fan Bao, Chongxuan Li, Jun Zhu |
| 2022 | EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Records. Gyubok Lee, Hyeonji Hwang, Seongsu Bae, Yeonsu Kwon, Woncheol Shin, Seongjun Yang, Minjoon Seo, Jong-Yeup Kim, Edward Choi |
| 2022 | ELASTIC: Numerical Reasoning with Adaptive Symbolic Compiler. Jiaxin Zhang, Yashar Moshfeghi |
| 2022 | ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models. Chunyuan Li, Haotian Liu, Liunian Harold Li, Pengchuan Zhang, Jyoti Aneja, Jianwei Yang, Ping Jin, Houdong Hu, Zicheng Liu, Yong Jae Lee, Jianfeng Gao |
| 2022 | ELIAS: End-to-End Learning to Index and Search in Large Output Spaces. Nilesh Gupta, Patrick H. Chen, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon |
| 2022 | ELIGN: Expectation Alignment as a Multi-Agent Intrinsic Reward. Zixian Ma, Rose E. Wang, Fei-Fei Li, Michael S. Bernstein, Ranjay Krishna |
| 2022 | ENS-10: A Dataset For Post-Processing Ensemble Weather Forecasts. Saleh Ashkboos, Langwen Huang, Nikoli Dryden, Tal Ben-Nun, Peter Dueben, Lukas Gianinazzi, Luca Kummer, Torsten Hoefler |
| 2022 | EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object Relations. Ahmad Darkhalil, Dandan Shan, Bin Zhu, Jian Ma, Amlan Kar, Richard E. L. Higgins, Sanja Fidler, David Fouhey, Dima Damen |
| 2022 | ESCADA: Efficient Safety and Context Aware Dose Allocation for Precision Medicine. Ilker Demirel, Ahmet Alparslan Celik, Cem Tekin |
| 2022 | ETAB: A Benchmark Suite for Visual Representation Learning in Echocardiography. Ahmed M. Alaa, Anthony Philippakis, David A. Sontag |
| 2022 | EZNAS: Evolving Zero-Cost Proxies For Neural Architecture Scoring. Yash Akhauri, Juan Pablo Muñoz, Nilesh Jain, Ravi Iyer |
| 2022 | Early Stage Convergence and Global Convergence of Training Mildly Parameterized Neural Networks. Mingze Wang, Chao Ma |
| 2022 | Earthformer: Exploring Space-Time Transformers for Earth System Forecasting. Zhihan Gao, Xingjian Shi, Hao Wang, Yi Zhu, Yuyang Wang, Mu Li, Dit-Yan Yeung |
| 2022 | EcoFormer: Energy-Saving Attention with Linear Complexity. Jing Liu, Zizheng Pan, Haoyu He, Jianfei Cai, Bohan Zhuang |
| 2022 | Effective Adaptation in Multi-Task Co-Training for Unified Autonomous Driving. Xiwen Liang, Yangxin Wu, Jianhua Han, Hang Xu, Chunjing Xu, Xiaodan Liang |
| 2022 | Effective Backdoor Defense by Exploiting Sensitivity of Poisoned Samples. Weixin Chen, Baoyuan Wu, Haoqian Wang |
| 2022 | Effective Dimension in Bandit Problems under Censorship. Gauthier Guinet, Saurabh Amin, Patrick Jaillet |
| 2022 | Effectiveness of Vision Transformer for Fast and Accurate Single-Stage Pedestrian Detection. Jing Yuan, Panagiotis Barmpoutis, Tania Stathaki |
| 2022 | Effects of Data Geometry in Early Deep Learning. Saket Tiwari, George Konidaris |
| 2022 | Efficiency Ordering of Stochastic Gradient Descent. Jie Hu, Vishwaraj Doshi, Do Young Eun |
| 2022 | Efficient Active Learning with Abstention. Yinglun Zhu, Robert Nowak |
| 2022 | Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learning. Yongyuan Liang, Yanchao Sun, Ruijie Zheng, Furong Huang |
| 2022 | Efficient Aggregated Kernel Tests using Incomplete $U$-statistics. Antonin Schrab, Ilmun Kim, Benjamin Guedj, Arthur Gretton |
| 2022 | Efficient Architecture Search for Diverse Tasks. Junhong Shen, Mikhail Khodak, Ameet Talwalkar |
| 2022 | Efficient Dataset Distillation using Random Feature Approximation. Noel Loo, Ramin M. Hasani, Alexander Amini, Daniela Rus |
| 2022 | Efficient Frameworks for Generalized Low-Rank Matrix Bandit Problems. Yue Kang, Cho-Jui Hsieh, Thomas Chun Man Lee |
| 2022 | Efficient Graph Similarity Computation with Alignment Regularization. Wei Zhuo, Guang Tan |
| 2022 | Efficient Knowledge Distillation from Model Checkpoints. Chaofei Wang, Qisen Yang, Rui Huang, Shiji Song, Gao Huang |
| 2022 | Efficient Meta Reinforcement Learning for Preference-based Fast Adaptation. Zhizhou Ren, Anji Liu, Yitao Liang, Jian Peng, Jianzhu Ma |
| 2022 | Efficient Methods for Non-stationary Online Learning. Peng Zhao, Yan-Feng Xie, Lijun Zhang, Zhi-Hua Zhou |
| 2022 | Efficient Multi-agent Communication via Self-supervised Information Aggregation. Cong Guan, Feng Chen, Lei Yuan, Chenghe Wang, Hao Yin, Zongzhang Zhang, Yang Yu |
| 2022 | Efficient Non-Parametric Optimizer Search for Diverse Tasks. Ruochen Wang, Yuanhao Xiong, Minhao Cheng, Cho-Jui Hsieh |
| 2022 | Efficient Phi-Regret Minimization in Extensive-Form Games via Online Mirror Descent. Yu Bai, Chi Jin, Song Mei, Ziang Song, Tiancheng Yu |
| 2022 | Efficient Risk-Averse Reinforcement Learning. Ido Greenberg, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor |
| 2022 | Efficient Sampling on Riemannian Manifolds via Langevin MCMC. Xiang Cheng, Jingzhao Zhang, Suvrit Sra |
| 2022 | Efficient Scheduling of Data Augmentation for Deep Reinforcement Learning. Byungchan Ko, Jungseul Ok |
| 2022 | Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models. Muyang Li, Ji Lin, Chenlin Meng, Stefano Ermon, Song Han, Jun-Yan Zhu |
| 2022 | Efficient Submodular Optimization under Noise: Local Search is Robust. Lingxiao Huang, Yuyi Wang, Chunxue Yang, Huanjian Zhou |
| 2022 | Efficient Training of Low-Curvature Neural Networks. Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju, François Fleuret |
| 2022 | Efficient and Effective Augmentation Strategy for Adversarial Training. Sravanti Addepalli, Samyak Jain, Venkatesh Babu R. |
| 2022 | Efficient and Effective Multi-task Grouping via Meta Learning on Task Combinations. Xiaozhuang Song, Shun Zheng, Wei Cao, James J. Q. Yu, Jiang Bian |
| 2022 | Efficient and Effective Optimal Transport-Based Biclustering. Chakib Fettal, Lazhar Labiod, Mohamed Nadif |
| 2022 | Efficient and Modular Implicit Differentiation. Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert |
| 2022 | Efficient and Near-Optimal Smoothed Online Learning for Generalized Linear Functions. Adam Block, Max Simchowitz |
| 2022 | Efficient and Stable Fully Dynamic Facility Location. Sayan Bhattacharya, Silvio Lattanzi, Nikos Parotsidis |
| 2022 | Efficient coding, channel capacity, and the emergence of retinal mosaics. Na Young Jun, Greg Field, John M. Pearson |
| 2022 | Efficient identification of informative features in simulation-based inference. Jonas Beck, Michael Deistler, Yves Bernaerts, Jakob H. Macke, Philipp Berens |
| 2022 | Efficient learning of nonlinear prediction models with time-series privileged information. Bastian Jung, Fredrik D. Johansson |
| 2022 | EfficientFormer: Vision Transformers at MobileNet Speed. Yanyu Li, Geng Yuan, Yang Wen, Ju Hu, Georgios Evangelidis, Sergey Tulyakov, Yanzhi Wang, Jian Ren |
| 2022 | Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation. Zhouxing Shi, Yihan Wang, Huan Zhang, J. Zico Kolter, Cho-Jui Hsieh |
| 2022 | Efficiently Factorizing Boolean Matrices using Proximal Gradient Descent. Sebastian Dalleiger, Jilles Vreeken |
| 2022 | EgoTaskQA: Understanding Human Tasks in Egocentric Videos. Baoxiong Jia, Ting Lei, Song-Chun Zhu, Siyuan Huang |
| 2022 | Egocentric Video-Language Pretraining. Kevin Qinghong Lin, Jinpeng Wang, Mattia Soldan, Michael Wray, Rui Yan, Eric Zhongcong Xu, Difei Gao, Rong-Cheng Tu, Wenzhe Zhao, Weijie Kong, Chengfei Cai, Hongfa Wang, Dima Damen, Bernard Ghanem, Wei Liu, Mike Zheng Shou |
| 2022 | ElasticMVS: Learning elastic part representation for self-supervised multi-view stereopsis. Jinzhi Zhang, Ruofan Tang, Zheng Cao, Jing Xiao, Ruqi Huang, Lu Fang |
| 2022 | Eliciting Thinking Hierarchy without a Prior. Yuqing Kong, Yunqi Li, Yubo Zhang, Zhihuan Huang, Jinzhao Wu |
| 2022 | Elucidating the Design Space of Diffusion-Based Generative Models. Tero Karras, Miika Aittala, Timo Aila, Samuli Laine |
| 2022 | Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification. Ruoxi Jiang, Rebecca Willett |
| 2022 | Embodied Scene-aware Human Pose Estimation. Zhengyi Luo, Shun Iwase, Ye Yuan, Kris Kitani |
| 2022 | Embrace the Gap: VAEs Perform Independent Mechanism Analysis. Patrik Reizinger, Luigi Gresele, Jack Brady, Julius von Kügelgen, Dominik Zietlow, Bernhard Schölkopf, Georg Martius, Wieland Brendel, Michel Besserve |
| 2022 | Embracing Consistency: A One-Stage Approach for Spatio-Temporal Video Grounding. Yang Jin, Yongzhi Li, Zehuan Yuan, Yadong Mu |
| 2022 | Emergence of Hierarchical Layers in a Single Sheet of Self-Organizing Spiking Neurons. Paul Bertens, Seong-Whan Lee |
| 2022 | Emergent Communication: Generalization and Overfitting in Lewis Games. Mathieu Rita, Corentin Tallec, Paul Michel, Jean-Bastien Grill, Olivier Pietquin, Emmanuel Dupoux, Florian Strub |
| 2022 | Emergent Graphical Conventions in a Visual Communication Game. Shuwen Qiu, Sirui Xie, Lifeng Fan, Tao Gao, Jungseock Joo, Song-Chun Zhu, Yixin Zhu |
| 2022 | Empirical Gateaux Derivatives for Causal Inference. Michael I. Jordan, Yixin Wang, Angela Zhou |
| 2022 | Empirical Phase Diagram for Three-layer Neural Networks with Infinite Width. Hanxu Zhou, Qixuan Zhou, Zhenyuan Jin, Tao Luo, Yaoyu Zhang, Zhi-Qin John Xu |
| 2022 | Enabling Detailed Action Recognition Evaluation Through Video Dataset Augmentation. Jihoon Chung, Yu Wu, Olga Russakovsky |
| 2022 | End-to-end Algorithm Synthesis with Recurrent Networks: Extrapolation without Overthinking. Arpit Bansal, Avi Schwarzschild, Eitan Borgnia, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein |
| 2022 | End-to-end Stochastic Optimization with Energy-based Model. Lingkai Kong, Jiaming Cui, Yuchen Zhuang, Rui Feng, B. Aditya Prakash, Chao Zhang |
| 2022 | End-to-end Symbolic Regression with Transformers. Pierre-Alexandre Kamienny, Stéphane d'Ascoli, Guillaume Lample, François Charton |
| 2022 | Energy-Based Contrastive Learning of Visual Representations. Beomsu Kim, Jong Chul Ye |
| 2022 | Enhance the Visual Representation via Discrete Adversarial Training. Xiaofeng Mao, Yuefeng Chen, Ranjie Duan, Yao Zhu, Gege Qi, Shaokai Ye, Xiaodan Li, Rong Zhang, Hui Xue |
| 2022 | Enhanced Bilevel Optimization via Bregman Distance. Feihu Huang, Junyi Li, Shangqian Gao, Heng Huang |
| 2022 | Enhanced Latent Space Blind Model for Real Image Denoising via Alternative Optimization. Chao Ren, Yizhong Pan, Jie Huang |
| 2022 | Enhanced Meta Reinforcement Learning via Demonstrations in Sparse Reward Environments. Desik Rengarajan, Sapana Chaudhary, Jaewon Kim, Dileep Kalathil, Srinivas Shakkottai |
| 2022 | Enhancing Safe Exploration Using Safety State Augmentation. Aivar Sootla, Alexander I. Cowen-Rivers, Jun Wang, Haitham Bou-Ammar |
| 2022 | Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalization. Devansh Arpit, Huan Wang, Yingbo Zhou, Caiming Xiong |
| 2022 | Entropy-Driven Mixed-Precision Quantization for Deep Network Design. Zhenhong Sun, Ce Ge, Junyan Wang, Ming Lin, Hesen Chen, Hao Li, Xiuyu Sun |
| 2022 | EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine. Jiayi Weng, Min Lin, Shengyi Huang, Bo Liu, Denys Makoviichuk, Viktor Makoviychuk, Zichen Liu, Yufan Song, Ting Luo, Yukun Jiang, Zhongwen Xu, Shuicheng Yan |
| 2022 | Environment Diversification with Multi-head Neural Network for Invariant Learning. Bo-Wei Huang, Keng-Te Liao, Chang-Sheng Kao, Shou-De Lin |
| 2022 | Envy-free Policy Teaching to Multiple Agents. Jiarui Gan, Rupak Majumdar, Adish Singla, Goran Radanovic |
| 2022 | EpiGRAF: Rethinking training of 3D GANs. Ivan Skorokhodov, Sergey Tulyakov, Yiqun Wang, Peter Wonka |
| 2022 | Equivariant Graph Hierarchy-Based Neural Networks. Jiaqi Han, Wenbing Huang, Tingyang Xu, Yu Rong |
| 2022 | Equivariant Networks for Crystal Structures. Sékou-Oumar Kaba, Siamak Ravanbakhsh |
| 2022 | Equivariant Networks for Zero-Shot Coordination. Darius Muglich, Christian Schröder de Witt, Elise van der Pol, Shimon Whiteson, Jakob N. Foerster |
| 2022 | Error Analysis of Tensor-Train Cross Approximation. Zhen Qin, Alexander Lidiak, Zhexuan Gong, Gongguo Tang, Michael B. Wakin, Zhihui Zhu |
| 2022 | Error Correction Code Transformer. Yoni Choukroun, Lior Wolf |
| 2022 | Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data. Harsh Rangwani, Sumukh K. Aithal, Mayank Mishra, Venkatesh Babu R. |
| 2022 | Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning. Tomoya Murata, Taiji Suzuki |
| 2022 | Escaping from the Barren Plateau via Gaussian Initializations in Deep Variational Quantum Circuits. Kaining Zhang, Liu Liu, Min-Hsiu Hsieh, Dacheng Tao |
| 2022 | Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning. Shikun Li, Xiaobo Xia, Hansong Zhang, Yibing Zhan, Shiming Ge, Tongliang Liu |
| 2022 | Estimating and Explaining Model Performance When Both Covariates and Labels Shift. Lingjiao Chen, Matei Zaharia, James Y. Zou |
| 2022 | Estimating graphical models for count data with applications to single-cell gene network. Feiyi Xiao, Junjie Tang, Huaying Fang, Ruibin Xi |
| 2022 | Estimating the Arc Length of the Optimal ROC Curve and Lower Bounding the Maximal AUC. Song Liu |
| 2022 | Estimation of Entropy in Constant Space with Improved Sample Complexity. Maryam Aliakbarpour, Andrew McGregor, Jelani Nelson, Erik Waingarten |
| 2022 | Evaluated CMI Bounds for Meta Learning: Tightness and Expressiveness. Fredrik Hellström, Giuseppe Durisi |
| 2022 | Evaluating Graph Generative Models with Contrastively Learned Features. Hamed Shirzad, Kaveh Hassani, Danica J. Sutherland |
| 2022 | Evaluating Latent Space Robustness and Uncertainty of EEG-ML Models under Realistic Distribution Shifts. Neeraj Wagh, Jionghao Wei, Samarth Rawal, Brent M. Berry, Yogatheesan Varatharajah |
| 2022 | Evaluating Out-of-Distribution Performance on Document Image Classifiers. Stefan Larson, Gordon Lim, Yutong Ai, David Kuang, Kevin Leach |
| 2022 | Evaluating Robustness to Dataset Shift via Parametric Robustness Sets. Nikolaj Thams, Michael Oberst, David A. Sontag |
| 2022 | Evaluation beyond Task Performance: Analyzing Concepts in AlphaZero in Hex. Charles Lovering, Jessica Forde, George Konidaris, Ellie Pavlick, Michael L. Littman |
| 2022 | EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks. Runlin Lei, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei |
| 2022 | Evolution of Neural Tangent Kernels under Benign and Adversarial Training. Noel Loo, Ramin M. Hasani, Alexander Amini, Daniela Rus |
| 2022 | Exact Shape Correspondence via 2D graph convolution. Barakeel Fanseu Kamhoua, Lin Zhang, Yongqiang Chen, Han Yang, Kaili Ma, Bo Han, Bo Li, James Cheng |
| 2022 | Exact Solutions of a Deep Linear Network. Liu Ziyin, Botao Li, Xiangming Meng |
| 2022 | Exact learning dynamics of deep linear networks with prior knowledge. Lukas Braun, Clémentine C. J. Dominé, James FitzGerald, Andrew M. Saxe |
| 2022 | Expansion and Shrinkage of Localization for Weakly-Supervised Semantic Segmentation. Jinlong Li, Zequn Jie, Xu Wang, Xiaolin Wei, Lin Ma |
| 2022 | Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations. Peng Jin, Jinfa Huang, Fenglin Liu, Xian Wu, Shen Ge, Guoli Song, David A. Clifton, Jie Chen |
| 2022 | Expected Frequency Matrices of Elections: Computation, Geometry, and Preference Learning. Niclas Boehmer, Robert Bredereck, Edith Elkind, Piotr Faliszewski, Stanislaw Szufa |
| 2022 | Expected Improvement for Contextual Bandits. Hung Tran-The, Sunil Gupta, Santu Rana, Tuan Truong, Long Tran-Thanh, Svetha Venkatesh |
| 2022 | Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning. Weicong Liang, Yuhui Yuan, Henghui Ding, Xiao Luo, Weihong Lin, Ding Jia, Zheng Zhang, Chao Zhang, Han Hu |
| 2022 | Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces. Mojmir Mutny, Andreas Krause |
| 2022 | Explain My Surprise: Learning Efficient Long-Term Memory by predicting uncertain outcomes. Artyom Y. Sorokin, Nazar Buzun, Leonid Pugachev, Mikhail Burtsev |
| 2022 | Explainability Via Causal Self-Talk. Nicholas A. Roy, Junkyung Kim, Neil C. Rabinowitz |
| 2022 | Explainable Reinforcement Learning via Model Transforms. Mira Finkelstein, Nitsan Levy Schlot, Lucy Liu, Yoav Kolumbus, David C. Parkes, Jeffrey S. Rosenschein, Sarah Keren |
| 2022 | Explaining Preferences with Shapley Values. Robert Hu, Siu Lun Chau, Jaime Ferrando Huertas, Dino Sejdinovic |
| 2022 | Explicable Policy Search. Ze Gong, Yu Zhang |
| 2022 | Explicit Tradeoffs between Adversarial and Natural Distributional Robustness. Mazda Moayeri, Kiarash Banihashem, Soheil Feizi |
| 2022 | Exploit Reward Shifting in Value-Based Deep-RL: Optimistic Curiosity-Based Exploration and Conservative Exploitation via Linear Reward Shaping. Hao Sun, Lei Han, Rui Yang, Xiaoteng Ma, Jian Guo, Bolei Zhou |
| 2022 | Exploitability Minimization in Games and Beyond. Denizalp Goktas, Amy Greenwald |
| 2022 | Exploiting Semantic Relations for Glass Surface Detection. Jiaying Lin, Yuen Hei Yeung, Rynson W. H. Lau |
| 2022 | Exploiting the Relationship Between Kendall's Rank Correlation and Cosine Similarity for Attribution Protection. Fan Wang, Adams Wai-Kin Kong |
| 2022 | Exploration via Elliptical Episodic Bonuses. Mikael Henaff, Roberta Raileanu, Minqi Jiang, Tim Rocktäschel |
| 2022 | Exploration via Planning for Information about the Optimal Trajectory. Viraj Mehta, Ian Char, Joseph Abbate, Rory Conlin, Mark D. Boyer, Stefano Ermon, Jeff Schneider, Willie Neiswanger |
| 2022 | Exploration-Guided Reward Shaping for Reinforcement Learning under Sparse Rewards. Rati Devidze, Parameswaran Kamalaruban, Adish Singla |
| 2022 | Exploring Example Influence in Continual Learning. Qing Sun, Fan Lyu, Fanhua Shang, Wei Feng, Liang Wan |
| 2022 | Exploring Figure-Ground Assignment Mechanism in Perceptual Organization. Wei Zhai, Yang Cao, Jing Zhang, Zheng-Jun Zha |
| 2022 | Exploring Length Generalization in Large Language Models. Cem Anil, Yuhuai Wu, Anders Andreassen, Aitor Lewkowycz, Vedant Misra, Vinay V. Ramasesh, Ambrose Slone, Guy Gur-Ari, Ethan Dyer, Behnam Neyshabur |
| 2022 | Exploring evolution-aware & -free protein language models as protein function predictors. Mingyang Hu, Fajie Yuan, Kevin Yang, Fusong Ju, Jin Su, Hui Wang, Fei Yang, Qiuyang Ding |
| 2022 | Exploring the Algorithm-Dependent Generalization of AUPRC Optimization with List Stability. Peisong Wen, Qianqian Xu, Zhiyong Yang, Yuan He, Qingming Huang |
| 2022 | Exploring the Latent Space of Autoencoders with Interventional Assays. Felix Leeb, Stefan Bauer, Michel Besserve, Bernhard Schölkopf |
| 2022 | Exploring the Limits of Domain-Adaptive Training for Detoxifying Large-Scale Language Models. Boxin Wang, Wei Ping, Chaowei Xiao, Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Bo Li, Anima Anandkumar, Bryan Catanzaro |
| 2022 | Exploring the Whole Rashomon Set of Sparse Decision Trees. Rui Xin, Chudi Zhong, Zhi Chen, Takuya Takagi, Margo I. Seltzer, Cynthia Rudin |
| 2022 | Exploring through Random Curiosity with General Value Functions. Aditya A. Ramesh, Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber |
| 2022 | Exponential Family Model-Based Reinforcement Learning via Score Matching. Gene Li, Junbo Li, Anmol Kabra, Nati Srebro, Zhaoran Wang, Zhuoran Yang |
| 2022 | Exponential Separations in Symmetric Neural Networks. Aaron Zweig, Joan Bruna |
| 2022 | Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks. Anders Aamand, Justin Y. Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner |
| 2022 | Exposing and Exploiting Fine-Grained Block Structures for Fast and Accurate Sparse Training. Peng Jiang, Lihan Hu, Shihui Song |
| 2022 | Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods. Kimon Antonakopoulos, Ali Kavis, Volkan Cevher |
| 2022 | Extracting computational mechanisms from neural data using low-rank RNNs. Adrian Valente, Jonathan W. Pillow, Srdjan Ostojic |
| 2022 | Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study. Yongtao Wu, Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher |
| 2022 | Extrapolative Continuous-time Bayesian Neural Network for Fast Training-free Test-time Adaptation. Hengguan Huang, Xiangming Gu, Hao Wang, Chang Xiao, Hongfu Liu, Ye Wang |
| 2022 | FACT: Learning Governing Abstractions Behind Integer Sequences. Peter Belcak, Ard Kastrati, Flavio Schenker, Roger Wattenhofer |
| 2022 | FETA: Towards Specializing Foundational Models for Expert Task Applications. Amit Alfassy, Assaf Arbelle, Oshri Halimi, Sivan Harary, Roei Herzig, Eli Schwartz, Rameswar Panda, Michele Dolfi, Christoph Auer, Peter W. J. Staar, Kate Saenko, Rogério Feris, Leonid Karlinsky |
| 2022 | FIRE: Semantic Field of Words Represented as Non-Linear Functions. Xin Du, Kumiko Tanaka-Ishii |
| 2022 | FLAIR: Federated Learning Annotated Image Repository. Congzheng Song, Filip Granqvist, Kunal Talwar |
| 2022 | FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers, Felix Grimberg, Chaoyang He, Regis Loeb, Paul Mangold, Tanguy Marchand, Othmane Marfoq, Erum Mushtaq, Boris Muzellec, Constantin Philippenko, Santiago Silva, Maria Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux |
| 2022 | FNeVR: Neural Volume Rendering for Face Animation. Bohan Zeng, Boyu Liu, Hong Li, Xuhui Liu, Jianzhuang Liu, Dapeng Chen, Wei Peng, Baochang Zhang |
| 2022 | FOF: Learning Fourier Occupancy Field for Monocular Real-time Human Reconstruction. Qiao Feng, Yebin Liu, Yu-Kun Lai, Jingyu Yang, Kun Li |
| 2022 | FP8 Quantization: The Power of the Exponent. Andrey Kuzmin, Mart van Baalen, Yuwei Ren, Markus Nagel, Jorn Peters, Tijmen Blankevoort |
| 2022 | FR: Folded Rationalization with a Unified Encoder. Wei Liu, Haozhao Wang, Jun Wang, Ruixuan Li, Chao Yue, Yuankai Zhang |
| 2022 | Factored Adaptation for Non-Stationary Reinforcement Learning. Fan Feng, Biwei Huang, Kun Zhang, Sara Magliacane |
| 2022 | Factored DRO: Factored Distributionally Robust Policies for Contextual Bandits. Tong Mu, Yash Chandak, Tatsunori B. Hashimoto, Emma Brunskill |
| 2022 | Factorized-FL: Personalized Federated Learning with Parameter Factorization & Similarity Matching. Wonyong Jeong, Sung Ju Hwang |
| 2022 | Factuality Enhanced Language Models for Open-Ended Text Generation. Nayeon Lee, Wei Ping, Peng Xu, Mostofa Patwary, Pascale Fung, Mohammad Shoeybi, Bryan Catanzaro |
| 2022 | Fair Bayes-Optimal Classifiers Under Predictive Parity. Xianli Zeng, Edgar Dobriban, Guang Cheng |
| 2022 | Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting. Prasanna Sattigeri, Soumya Ghosh, Inkit Padhi, Pierre L. Dognin, Kush R. Varshney |
| 2022 | Fair Rank Aggregation. Diptarka Chakraborty, Syamantak Das, Arindam Khan, Aditya Subramanian |
| 2022 | Fair Ranking with Noisy Protected Attributes. Anay Mehrotra, Nisheeth K. Vishnoi |
| 2022 | Fair Wrapping for Black-box Predictions. Alexander Soen, Ibrahim M. Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi, Richard Nock, Ke Sun, Lexing Xie |
| 2022 | Fair and Efficient Allocations Without Obvious Manipulations. Alexandros Psomas, Paritosh Verma |
| 2022 | Fair and Optimal Decision Trees: A Dynamic Programming Approach. Jacobus G. M. van der Linden, Mathijs de Weerdt, Emir Demirovic |
| 2022 | FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning. Tao Qi, Fangzhao Wu, Chuhan Wu, Lingjuan Lyu, Tong Xu, Hao Liao, Zhongliang Yang, Yongfeng Huang, Xing Xie |
| 2022 | Fairness Reprogramming. Guanhua Zhang, Yihua Zhang, Yang Zhang, Wenqi Fan, Qing Li, Sijia Liu, Shiyu Chang |
| 2022 | Fairness Transferability Subject to Bounded Distribution Shift. Yatong Chen, Reilly Raab, Jialu Wang, Yang Liu |
| 2022 | Fairness in Federated Learning via Core-Stability. Bhaskar Ray Chaudhury, Linyi Li, Mintong Kang, Bo Li, Ruta Mehta |
| 2022 | Fairness without Demographics through Knowledge Distillation. Junyi Chai, Taeuk Jang, Xiaoqian Wang |
| 2022 | Falconn++: A Locality-sensitive Filtering Approach for Approximate Nearest Neighbor Search. Ninh Pham, Tao Liu |
| 2022 | Falsification before Extrapolation in Causal Effect Estimation. Zeshan M. Hussain, Michael Oberst, Ming-Chieh Shih, David A. Sontag |
| 2022 | Fast Algorithms for Packing Proportional Fairness and its Dual. Francisco Criado, David Martínez-Rubio, Sebastian Pokutta |
| 2022 | Fast Bayesian Coresets via Subsampling and Quasi-Newton Refinement. Cian Naik, Judith Rousseau, Trevor Campbell |
| 2022 | Fast Bayesian Estimation of Point Process Intensity as Function of Covariates. Hideaki Kim, Taichi Asami, Hiroyuki Toda |
| 2022 | Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination. Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser, Michael A. Osborne |
| 2022 | Fast Distance Oracles for Any Symmetric Norm. Yichuan Deng, Zhao Song, Omri Weinstein, Ruizhe Zhang |
| 2022 | Fast Instrument Learning with Faster Rates. Ziyu Wang, Yuhao Zhou, Jun Zhu |
| 2022 | Fast Mixing of Stochastic Gradient Descent with Normalization and Weight Decay. Zhiyuan Li, Tianhao Wang, Dingli Yu |
| 2022 | Fast Neural Kernel Embeddings for General Activations. Insu Han, Amir Zandieh, Jaehoon Lee, Roman Novak, Lechao Xiao, Amin Karbasi |
| 2022 | Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization. Benjamin Dubois-Taine, Francis R. Bach, Quentin Berthet, Adrien B. Taylor |
| 2022 | Fast Vision Transformers with HiLo Attention. Zizheng Pan, Jianfei Cai, Bohan Zhuang |
| 2022 | Faster Deep Reinforcement Learning with Slower Online Network. Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Taesup Kim, Michael L. Littman, Alexander J. Smola |
| 2022 | Faster Linear Algebra for Distance Matrices. Piotr Indyk, Sandeep Silwal |
| 2022 | Faster Stochastic Algorithms for Minimax Optimization under Polyak-{\L}ojasiewicz Condition. Lesi Chen, Boyuan Yao, Luo Luo |
| 2022 | Faster and Scalable Algorithms for Densest Subgraph and Decomposition. Elfarouk Harb, Kent Quanrud, Chandra Chekuri |
| 2022 | FasterRisk: Fast and Accurate Interpretable Risk Scores. Jiachang Liu, Chudi Zhong, Boxuan Li, Margo I. Seltzer, Cynthia Rudin |
| 2022 | Fault-Aware Neural Code Rankers. Jeevana Priya Inala, Chenglong Wang, Mei Yang, Andrés Codas, Mark Encarnación, Shuvendu K. Lahiri, Madanlal Musuvathi, Jianfeng Gao |
| 2022 | FeLMi : Few shot Learning with hard Mixup. Aniket Roy, Anshul Shah, Ketul Shah, Prithviraj Dhar, Anoop Cherian, Rama Chellappa |
| 2022 | Feature Learning in $L_2$-regularized DNNs: Attraction/Repulsion and Sparsity. Arthur Jacot, Eugene A. Golikov, Clément Hongler, Franck Gabriel |
| 2022 | Feature-Proxy Transformer for Few-Shot Segmentation. Jian-Wei Zhang, Yifan Sun, Yi Yang, Wei Chen |
| 2022 | FedAvg with Fine Tuning: Local Updates Lead to Representation Learning. Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai |
| 2022 | FedPop: A Bayesian Approach for Personalised Federated Learning. Nikita Kotelevskii, Maxime Vono, Alain Durmus, Eric Moulines |
| 2022 | FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction. Samiul Alam, Luyang Liu, Ming Yan, Mi Zhang |
| 2022 | FedSR: A Simple and Effective Domain Generalization Method for Federated Learning. A. Tuan Nguyen, Philip H. S. Torr, Ser Nam Lim |
| 2022 | Federated Learning from Pre-Trained Models: A Contrastive Learning Approach. Yue Tan, Guodong Long, Jie Ma, Lu Liu, Tianyi Zhou, Jing Jiang |
| 2022 | Federated Submodel Optimization for Hot and Cold Data Features. Yucheng Ding, Chaoyue Niu, Fan Wu, Shaojie Tang, Chengfei Lyu, Yanghe Feng, Guihai Chen |
| 2022 | Few-Shot Audio-Visual Learning of Environment Acoustics. Sagnik Majumder, Changan Chen, Ziad Al-Halah, Kristen Grauman |
| 2022 | Few-Shot Continual Active Learning by a Robot. Ali Ayub, Carter Fendley |
| 2022 | Few-Shot Fast-Adaptive Anomaly Detection. Ze Wang, Yipin Zhou, Rui Wang, Tsung-Yu Lin, Ashish Shah, Ser Nam Lim |
| 2022 | Few-Shot Non-Parametric Learning with Deep Latent Variable Model. Zhiying Jiang, Yiqin Dai, Ji Xin, Ming Li, Jimmy Lin |
| 2022 | Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning. Haokun Liu, Derek Tam, Mohammed Muqeeth, Jay Mohta, Tenghao Huang, Mohit Bansal, Colin Raffel |
| 2022 | Few-shot Image Generation via Adaptation-Aware Kernel Modulation. Yunqing Zhao, Keshigeyan Chandrasegaran, Milad Abdollahzadeh, Ngai-Man Cheung |
| 2022 | Few-shot Learning for Feature Selection with Hilbert-Schmidt Independence Criterion. Atsutoshi Kumagai, Tomoharu Iwata, Yasutoshi Ida, Yasuhiro Fujiwara |
| 2022 | Few-shot Relational Reasoning via Connection Subgraph Pretraining. Qian Huang, Hongyu Ren, Jure Leskovec |
| 2022 | Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models. Dongkuan Xu, Subhabrata Mukherjee, Xiaodong Liu, Debadeepta Dey, Wenhui Wang, Xiang Zhang, Ahmed Hassan Awadallah, Jianfeng Gao |
| 2022 | FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear Modulation. Mehmet Ozgur Turkoglu, Alexander Becker, Hüseyin Anil Gündüz, Mina Rezaei, Bernd Bischl, Rodrigo Caye Daudt, Stefano D'Aronco, Jan D. Wegner, Konrad Schindler |
| 2022 | FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting. Tian Zhou, Ziqing Ma, Xue Wang, Qingsong Wen, Liang Sun, Tao Yao, Wotao Yin, Rong Jin |
| 2022 | FinRL-Meta: Market Environments and Benchmarks for Data-Driven Financial Reinforcement Learning. Xiao-Yang Liu, Ziyi Xia, Jingyang Rui, Jiechao Gao, Hongyang Yang, Ming Zhu, Christina Dan Wang, Zhaoran Wang, Jian Guo |
| 2022 | Finding Correlated Equilibrium of Constrained Markov Game: A Primal-Dual Approach. Ziyi Chen, Shaocong Ma, Yi Zhou |
| 2022 | Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing. Nataniel Ruiz, Sarah A. Bargal, Cihang Xie, Kate Saenko, Stan Sclaroff |
| 2022 | Finding Naturally Occurring Physical Backdoors in Image Datasets. Emily Wenger, Roma Bhattacharjee, Arjun Nitin Bhagoji, Josephine Passananti, Emilio Andere, Heather Zheng, Ben Y. Zhao |
| 2022 | Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget. Jasmin Brandt, Viktor Bengs, Björn Haddenhorst, Eyke Hüllermeier |
| 2022 | Finding Second-Order Stationary Points in Nonconvex-Strongly-Concave Minimax Optimization. Luo Luo, Yujun Li, Cheng Chen |
| 2022 | Finding and Listing Front-door Adjustment Sets. Hyunchai Jeong, Jin Tian, Elias Bareinboim |
| 2022 | Fine-Grained Analysis of Stability and Generalization for Modern Meta Learning Algorithms. Jiechao Guan, Yong Liu, Zhiwu Lu |
| 2022 | Fine-Grained Semantically Aligned Vision-Language Pre-Training. Juncheng Li, Xin He, Longhui Wei, Long Qian, Linchao Zhu, Lingxi Xie, Yueting Zhuang, Qi Tian, Siliang Tang |
| 2022 | Fine-Tuning Pre-Trained Language Models Effectively by Optimizing Subnetworks Adaptively. Haojie Zhang, Ge Li, Jia Li, Zhongjin Zhang, Yuqi Zhu, Zhi Jin |
| 2022 | Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees. Jue Wang, Binhang Yuan, Luka Rimanic, Yongjun He, Tri Dao, Beidi Chen, Christopher Ré, Ce Zhang |
| 2022 | Fine-tuning language models to find agreement among humans with diverse preferences. Michiel A. Bakker, Martin J. Chadwick, Hannah Sheahan, Michael Henry Tessler, Lucy Campbell-Gillingham, Jan Balaguer, Nat McAleese, Amelia Glaese, John Aslanides, Matt M. Botvinick, Christopher Summerfield |
| 2022 | Finite Sample Analysis Of Dynamic Regression Parameter Learning. Mark Kozdoba, Edward Moroshko, Shie Mannor, Yacov Crammer |
| 2022 | Finite-Sample Maximum Likelihood Estimation of Location. Shivam Gupta, Jasper C. H. Lee, Eric Price, Paul Valiant |
| 2022 | Finite-Time Analysis of Adaptive Temporal Difference Learning with Deep Neural Networks. Tao Sun, Dongsheng Li, Bao Wang |
| 2022 | Finite-Time Last-Iterate Convergence for Learning in Multi-Player Games. Yang Cai, Argyris Oikonomou, Weiqiang Zheng |
| 2022 | Finite-Time Regret of Thompson Sampling Algorithms for Exponential Family Multi-Armed Bandits. Tianyuan Jin, Pan Xu, Xiaokui Xiao, Anima Anandkumar |
| 2022 | First Contact: Unsupervised Human-Machine Co-Adaptation via Mutual Information Maximization. Siddharth Reddy, Sergey Levine, Anca D. Dragan |
| 2022 | First Hitting Diffusion Models for Generating Manifold, Graph and Categorical Data. Mao Ye, Lemeng Wu, Qiang Liu |
| 2022 | First is Better Than Last for Language Data Influence. Chih-Kuan Yeh, Ankur Taly, Mukund Sundararajan, Frederick Liu, Pradeep Ravikumar |
| 2022 | First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces. Michael I. Jordan, Tianyi Lin, Emmanouil V. Vlatakis-Gkaragkounis |
| 2022 | Fixed-Distance Hamiltonian Monte Carlo. Hadi Mohasel Afshar, Sally Cripps |
| 2022 | Flamingo: a Visual Language Model for Few-Shot Learning. Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katherine Millican, Malcolm Reynolds, Roman Ring, Eliza Rutherford, Serkan Cabi, Tengda Han, Zhitao Gong, Sina Samangooei, Marianne Monteiro, Jacob L. Menick, Sebastian Borgeaud, Andy Brock, Aida Nematzadeh, Sahand Sharifzadeh, Mikolaj Binkowski, Ricardo Barreira, Oriol Vinyals, Andrew Zisserman, Karén Simonyan |
| 2022 | Flare7K: A Phenomenological Nighttime Flare Removal Dataset. Yuekun Dai, Chongyi Li, Shangchen Zhou, Ruicheng Feng, Chen Change Loy |
| 2022 | FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness. Tri Dao, Daniel Y. Fu, Stefano Ermon, Atri Rudra, Christopher Ré |
| 2022 | Flexible Diffusion Modeling of Long Videos. William Harvey, Saeid Naderiparizi, Vaden Masrani, Christian Weilbach, Frank Wood |
| 2022 | Flexible Neural Image Compression via Code Editing. Chenjian Gao, Tongda Xu, Dailan He, Yan Wang, Hongwei Qin |
| 2022 | FlowHMM: Flow-based continuous hidden Markov models. Pawel Lorek, Rafal Nowak, Tomasz Trzcinski, Maciej Zieba |
| 2022 | Flowification: Everything is a normalizing flow. Bálint Máté, Samuel Klein, Tobias Golling, François Fleuret |
| 2022 | FlyView: a bio-informed optical flow truth dataset for visual navigation using panoramic stereo vision. Alix Leroy, Graham K. Taylor |
| 2022 | Focal Modulation Networks. Jianwei Yang, Chunyuan Li, Xiyang Dai, Jianfeng Gao |
| 2022 | Follow-the-Perturbed-Leader for Adversarial Markov Decision Processes with Bandit Feedback. Yan Dai, Haipeng Luo, Liyu Chen |
| 2022 | Forecasting Future World Events With Neural Networks. Andy Zou, Tristan Xiao, Ryan Jia, Joe Kwon, Mantas Mazeika, Richard Li, Dawn Song, Jacob Steinhardt, Owain Evans, Dan Hendrycks |
| 2022 | Forecasting Human Trajectory from Scene History. Mancheng Meng, Ziyan Wu, Terrence Chen, Xiran Cai, Xiang Sean Zhou, Fan Yang, Dinggang Shen |
| 2022 | Formalizing Consistency and Coherence of Representation Learning. Harald Strömfelt, Luke Dickens, Artur S. d'Avila Garcez, Alessandra Russo |
| 2022 | Formulating Robustness Against Unforeseen Attacks. Sihui Dai, Saeed Mahloujifar, Prateek Mittal |
| 2022 | Forward-Backward Latent State Inference for Hidden Continuous-Time semi-Markov Chains. Nicolai Engelmann, Heinz Koeppl |
| 2022 | Foundation Posteriors for Approximate Probabilistic Inference. Mike Wu, Noah D. Goodman |
| 2022 | FourierFormer: Transformer Meets Generalized Fourier Integral Theorem. Tan Nguyen, Minh Pham, Tam Nguyen, Khai Nguyen, Stanley J. Osher, Nhat Ho |
| 2022 | FourierNets enable the design of highly non-local optical encoders for computational imaging. Diptodip Deb, Zhenfei Jiao, Ruth R. Sims, Alex B. Chen, Michael Broxton, Misha B. Ahrens, Kaspar Podgorski, Srinivas C. Turaga |
| 2022 | Frank-Wolfe-based Algorithms for Approximating Tyler's M-estimator. Lior Danon, Dan Garber |
| 2022 | FreGAN: Exploiting Frequency Components for Training GANs under Limited Data. Mengping Yang, Zhe Wang, Ziqiu Chi, Yanbing Zhang |
| 2022 | Free Probability for predicting the performance of feed-forward fully connected neural networks. Reda Chhaibi, Tariq Daouda, Ezechiel Kahn |
| 2022 | Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attack. Tian Yu Liu, Yu Yang, Baharan Mirzasoleiman |
| 2022 | From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent. Christopher De Sa, Satyen Kale, Jason D. Lee, Ayush Sekhari, Karthik Sridharan |
| 2022 | Fully Convolutional One-Stage 3D Object Detection on LiDAR Range Images. Zhi Tian, Xiangxiang Chu, Xiaoming Wang, Xiaolin Wei, Chunhua Shen |
| 2022 | Fully Sparse 3D Object Detection. Lue Fan, Feng Wang, Naiyan Wang, Zhaoxiang Zhang |
| 2022 | Function Classes for Identifiable Nonlinear Independent Component Analysis. Simon Buchholz, Michel Besserve, Bernhard Schölkopf |
| 2022 | Functional Ensemble Distillation. Coby Penso, Idan Achituve, Ethan Fetaya |
| 2022 | Functional Indirection Neural Estimator for Better Out-of-distribution Generalization. Kha Pham, Hung Le, Man Ngo, Truyen Tran |
| 2022 | Fused Orthogonal Alternating Least Squares for Tensor Clustering. Jiacheng Wang, Dan Nicolae |
| 2022 | Fuzzy Learning Machine. Junbiao Cui, Jiye Liang |
| 2022 | GAGA: Deciphering Age-path of Generalized Self-paced Regularizer. Xingyu Qu, Diyang Li, Xiaohan Zhao, Bin Gu |
| 2022 | GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations. Enmao Diao, Jie Ding, Vahid Tarokh |
| 2022 | GALOIS: Boosting Deep Reinforcement Learning via Generalizable Logic Synthesis. Yushi Cao, Zhiming Li, Tianpei Yang, Hao Zhang, Yan Zheng, Yi Li, Jianye Hao, Yang Liu |
| 2022 | GAMA: Generative Adversarial Multi-Object Scene Attacks. Abhishek Aich, Calvin-Khang Ta, Akash Gupta, Chengyu Song, Srikanth V. Krishnamurthy, M. Salman Asif, Amit Roy-Chowdhury |
| 2022 | GAPX: Generalized Autoregressive Paraphrase-Identification X. Yifei Zhou, Renyu Li, Hayden Housen, Ser Nam Lim |
| 2022 | GAR: Generalized Autoregression for Multi-Fidelity Fusion. Yuxin Wang, Zheng Xing, Wei W. Xing |
| 2022 | GAUDI: A Neural Architect for Immersive 3D Scene Generation. Miguel Ángel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott, Alexander Toshev, Zhuoyuan Chen, Laurent Dinh, Shuangfei Zhai, Hanlin Goh, Daniel Ulbricht, Afshin Dehghan, Joshua M. Susskind |
| 2022 | GBA: A Tuning-free Approach to Switch between Synchronous and Asynchronous Training for Recommendation Models. Wenbo Su, Yuanxing Zhang, Yufeng Cai, Kaixu Ren, Pengjie Wang, Huimin Yi, Yue Song, Jing Chen, Hongbo Deng, Jian Xu, Lin Qu, Bo Zheng |
| 2022 | GENIE: Higher-Order Denoising Diffusion Solvers. Tim Dockhorn, Arash Vahdat, Karsten Kreis |
| 2022 | GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images. Jun Gao, Tianchang Shen, Zian Wang, Wenzheng Chen, Kangxue Yin, Daiqing Li, Or Litany, Zan Gojcic, Sanja Fidler |
| 2022 | GLIF: A Unified Gated Leaky Integrate-and-Fire Neuron for Spiking Neural Networks. Xingting Yao, Fanrong Li, Zitao Mo, Jian Cheng |
| 2022 | GLIPv2: Unifying Localization and Vision-Language Understanding. Haotian Zhang, Pengchuan Zhang, Xiaowei Hu, Yen-Chun Chen, Liunian Harold Li, Xiyang Dai, Lijuan Wang, Lu Yuan, Jenq-Neng Hwang, Jianfeng Gao |
| 2022 | GLOBEM Dataset: Multi-Year Datasets for Longitudinal Human Behavior Modeling Generalization. Xuhai Xu, Han Zhang, Yasaman S. Sefidgar, Yiyi Ren, Xin Liu, Woosuk Seo, Jennifer Brown, Kevin S. Kuehn, Mike A. Merrill, Paula S. Nurius, Shwetak N. Patel, Tim Althoff, Margaret E. Morris, Eve A. Riskin, Jennifer Mankoff, Anind K. Dey |
| 2022 | GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models. Chen Liang, Wenguan Wang, Jiaxu Miao, Yi Yang |
| 2022 | GOOD: A Graph Out-of-Distribution Benchmark. Shurui Gui, Xiner Li, Limei Wang, Shuiwang Ji |
| 2022 | GPT3.int8(): 8-bit Matrix Multiplication for Transformers at Scale. Tim Dettmers, Mike Lewis, Younes Belkada, Luke Zettlemoyer |
| 2022 | GRASP: Navigating Retrosynthetic Planning with Goal-driven Policy. Yemin Yu, Ying Wei, Kun Kuang, Zhengxing Huang, Huaxiu Yao, Fei Wu |
| 2022 | GREED: A Neural Framework for Learning Graph Distance Functions. Rishabh Ranjan, Siddharth Grover, Sourav Medya, Venkatesan T. Chakaravarthy, Yogish Sabharwal, Sayan Ranu |
| 2022 | GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games. Shichang Zhang, Yozen Liu, Neil Shah, Yizhou Sun |
| 2022 | GT-GAN: General Purpose Time Series Synthesis with Generative Adversarial Networks. Jinsung Jeon, Jeonghak Kim, Haryong Song, Seunghyeon Cho, Noseong Park |
| 2022 | GULP: a prediction-based metric between representations. Enric Boix-Adserà, Hannah Lawrence, George Stepaniants, Philippe Rigollet |
| 2022 | Gaussian Copula Embeddings. Chien Lu, Jaakko Peltonen |
| 2022 | GenSDF: Two-Stage Learning of Generalizable Signed Distance Functions. Gene Chou, Ilya Chugunov, Felix Heide |
| 2022 | GenerSpeech: Towards Style Transfer for Generalizable Out-Of-Domain Text-to-Speech. Rongjie Huang, Yi Ren, Jinglin Liu, Chenye Cui, Zhou Zhao |
| 2022 | General Cutting Planes for Bound-Propagation-Based Neural Network Verification. Huan Zhang, Shiqi Wang, Kaidi Xu, Linyi Li, Bo Li, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter |
| 2022 | Generalised Implicit Neural Representations. Daniele Grattarola, Pierre Vandergheynst |
| 2022 | Generalised Mutual Information for Discriminative Clustering. Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Warith Harchaoui, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso |
| 2022 | Generalization Analysis of Message Passing Neural Networks on Large Random Graphs. Sohir Maskey, Ron Levie, Yunseok Lee, Gitta Kutyniok |
| 2022 | Generalization Analysis on Learning with a Concurrent Verifier. Masaaki Nishino, Kengo Nakamura, Norihito Yasuda |
| 2022 | Generalization Bounds for Estimating Causal Effects of Continuous Treatments. Xin Wang, Shengfei Lyu, Xingyu Wu, Tianhao Wu, Huanhuan Chen |
| 2022 | Generalization Bounds for Gradient Methods via Discrete and Continuous Prior. Xuanyuan Luo, Bei Luo, Jian Li |
| 2022 | Generalization Bounds for Stochastic Gradient Descent via Localized $\varepsilon$-Covers. Sejun Park, Umut Simsekli, Murat A. Erdogdu |
| 2022 | Generalization Bounds with Minimal Dependency on Hypothesis Class via Distributionally Robust Optimization. Yibo Zeng, Henry Lam |
| 2022 | Generalization Error Bounds on Deep Learning with Markov Datasets. Lan V. Truong |
| 2022 | Generalization Gap in Amortized Inference. Mingtian Zhang, Peter Hayes, David Barber |
| 2022 | Generalization Properties of NAS under Activation and Skip Connection Search. Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher |
| 2022 | Generalization for multiclass classification with overparameterized linear models. Vignesh Subramanian, Rahul Arya, Anant Sahai |
| 2022 | Generalized Delayed Feedback Model with Post-Click Information in Recommender Systems. Jia-Qi Yang, De-Chuan Zhan |
| 2022 | Generalized Laplacian Eigenmaps. Hao Zhu, Piotr Koniusz |
| 2022 | Generalized One-shot Domain Adaptation of Generative Adversarial Networks. Zicheng Zhang, Yinglu Liu, Congying Han, Tiande Guo, Ting Yao, Tao Mei |
| 2022 | Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning. Veit D. Wild, Robert Hu, Dino Sejdinovic |
| 2022 | Generalizing Bayesian Optimization with Decision-theoretic Entropies. Willie Neiswanger, Lantao Yu, Shengjia Zhao, Chenlin Meng, Stefano Ermon |
| 2022 | Generalizing Consistent Multi-Class Classification with Rejection to be Compatible with Arbitrary Losses. Yuzhou Cao, Tianchi Cai, Lei Feng, Lihong Gu, Jinjie Gu, Bo An, Gang Niu, Masashi Sugiyama |
| 2022 | Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning. Wenhao Ding, Haohong Lin, Bo Li, Ding Zhao |
| 2022 | Generating Long Videos of Dynamic Scenes. Tim Brooks, Janne Hellsten, Miika Aittala, Ting-Chun Wang, Timo Aila, Jaakko Lehtinen, Ming-Yu Liu, Alexei A. Efros, Tero Karras |
| 2022 | Generating Training Data with Language Models: Towards Zero-Shot Language Understanding. Yu Meng, Jiaxin Huang, Yu Zhang, Jiawei Han |
| 2022 | Generating multivariate time series with COmmon Source CoordInated GAN (COSCI-GAN). Ali Seyfi, Jean-François Rajotte, Raymond T. Ng |
| 2022 | Generative Neural Articulated Radiance Fields. Alexander W. Bergman, Petr Kellnhofer, Wang Yifan, Eric R. Chan, David B. Lindell, Gordon Wetzstein |
| 2022 | Generative Status Estimation and Information Decoupling for Image Rain Removal. Di Lin, Xin Wang, Jia Shen, Renjie Zhang, Ruonan Liu, Miaohui Wang, Wuyuan Xie, Qing Guo, Ping Li |
| 2022 | Generative Time Series Forecasting with Diffusion, Denoise, and Disentanglement. Yan Li, Xinjiang Lu, Yaqing Wang, Dejing Dou |
| 2022 | Generative Visual Prompt: Unifying Distributional Control of Pre-Trained Generative Models. Chen Henry Wu, Saman Motamed, Shaunak Srivastava, Fernando De la Torre |
| 2022 | Generative multitask learning mitigates target-causing confounding. Taro Makino, Krzysztof J. Geras, Kyunghyun Cho |
| 2022 | Generic bounds on the approximation error for physics-informed (and) operator learning. Tim De Ryck, Siddhartha Mishra |
| 2022 | Geo-Neus: Geometry-Consistent Neural Implicit Surfaces Learning for Multi-view Reconstruction. Qiancheng Fu, Qingshan Xu, Yew Soon Ong, Wenbing Tao |
| 2022 | Geo-SIC: Learning Deformable Geometric Shapes in Deep Image Classifiers. Jian Wang, Miaomiao Zhang |
| 2022 | Geoclidean: Few-Shot Generalization in Euclidean Geometry. Joy Hsu, Jiajun Wu, Noah D. Goodman |
| 2022 | Geodesic Graph Neural Network for Efficient Graph Representation Learning. Lecheng Kong, Yixin Chen, Muhan Zhang |
| 2022 | Geodesic Self-Attention for 3D Point Clouds. Zhengyu Li, Xuan Tang, Zihao Xu, Xihao Wang, Hui Yu, Mingsong Chen, Xian Wei |
| 2022 | Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks. Chenxiao Yang, Qitian Wu, Junchi Yan |
| 2022 | Geometric Order Learning for Rank Estimation. Seon-Ho Lee, Nyeong-Ho Shin, Chang-Su Kim |
| 2022 | Geometry-aware Two-scale PIFu Representation for Human Reconstruction. Zheng Dong, Ke Xu, Ziheng Duan, Hujun Bao, Weiwei Xu, Rynson W. H. Lau |
| 2022 | Get More at Once: Alternating Sparse Training with Gradient Correction. Li Yang, Jian Meng, Jae-sun Seo, Deliang Fan |
| 2022 | GhostNetV2: Enhance Cheap Operation with Long-Range Attention. Yehui Tang, Kai Han, Jianyuan Guo, Chang Xu, Chao Xu, Yunhe Wang |
| 2022 | Giga-scale Kernel Matrix-Vector Multiplication on GPU. Robert Hu, Siu Lun Chau, Dino Sejdinovic, Joan Glaunès |
| 2022 | Giving Feedback on Interactive Student Programs with Meta-Exploration. Evan Zheran Liu, Moritz Stephan, Allen Nie, Chris Piech, Emma Brunskill, Chelsea Finn |
| 2022 | GlanceNets: Interpretable, Leak-proof Concept-based Models. Emanuele Marconato, Andrea Passerini, Stefano Teso |
| 2022 | Global Convergence and Stability of Stochastic Gradient Descent. Vivak Patel, Shushu Zhang, Bowen Tian |
| 2022 | Global Convergence of Direct Policy Search for State-Feedback $\mathcal{H}_\infty$ Robust Control: A Revisit of Nonsmooth Synthesis with Goldstein Subdifferential. Xingang Guo, Bin Hu |
| 2022 | Global Convergence of Federated Learning for Mixed Regression. Lili Su, Jiaming Xu, Pengkun Yang |
| 2022 | Global Linear and Local Superlinear Convergence of IRLS for Non-Smooth Robust Regression. Liangzu Peng, Christian Kümmerle, René Vidal |
| 2022 | Global Normalization for Streaming Speech Recognition in a Modular Framework. Ehsan Variani, Ke Wu, Michael D. Riley, David Rybach, Matt Shannon, Cyril Allauzen |
| 2022 | Global Optimal K-Medoids Clustering of One Million Samples. Jiayang Ren, Kaixun Hua, Yankai Cao |
| 2022 | Globally Convergent Policy Search for Output Estimation. Jack Umenberger, Max Simchowitz, Juan C. Perdomo, Kaiqing Zhang, Russ Tedrake |
| 2022 | Globally Gated Deep Linear Networks. Qianyi Li, Haim Sompolinsky |
| 2022 | Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need? Leon Gerard, Michael Scherbela, Philipp Marquetand, Philipp Grohs |
| 2022 | GraB: Finding Provably Better Data Permutations than Random Reshuffling. Yucheng Lu, Wentao Guo, Christopher De Sa |
| 2022 | Gradient Descent Is Optimal Under Lower Restricted Secant Inequality And Upper Error Bound. Charles Guille-Escuret, Adam Ibrahim, Baptiste Goujaud, Ioannis Mitliagkas |
| 2022 | Gradient Descent: The Ultimate Optimizer. Kartik Chandra, Audrey Xie, Jonathan Ragan-Kelley, Erik Meijer |
| 2022 | Gradient Estimation with Discrete Stein Operators. Jiaxin Shi, Yuhao Zhou, Jessica Hwang, Michalis K. Titsias, Lester Mackey |
| 2022 | Gradient Methods Provably Converge to Non-Robust Networks. Gal Vardi, Gilad Yehudai, Ohad Shamir |
| 2022 | Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs. Etienne Boursier, Loucas Pillaud-Vivien, Nicolas Flammarion |
| 2022 | Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization. Tianyi Lin, Zeyu Zheng, Michael I. Jordan |
| 2022 | Graph Coloring via Neural Networks for Haplotype Assembly and Viral Quasispecies Reconstruction. Hansheng Xue, Vaibhav Rajan, Yu Lin |
| 2022 | Graph Convolution Network based Recommender Systems: Learning Guarantee and Item Mixture Powered Strategy. Leyan Deng, Defu Lian, Chenwang Wu, Enhong Chen |
| 2022 | Graph Few-shot Learning with Task-specific Structures. Song Wang, Chen Chen, Jundong Li |
| 2022 | Graph Learning Assisted Multi-Objective Integer Programming. Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang, Abhishek Gupta, Mingyan Lin |
| 2022 | Graph Neural Network Bandits. Parnian Kassraie, Andreas Krause, Ilija Bogunovic |
| 2022 | Graph Neural Networks are Dynamic Programmers. Andrew Joseph Dudzik, Petar Velickovic |
| 2022 | Graph Neural Networks with Adaptive Readouts. David Buterez, Jon Paul Janet, Steven J. Kiddle, Dino Oglic, Pietro Liò |
| 2022 | Graph Reordering for Cache-Efficient Near Neighbor Search. Benjamin Coleman, Santiago Segarra, Alexander J. Smola, Anshumali Shrivastava |
| 2022 | Graph Scattering beyond Wavelet Shackles. Christian Koke, Gitta Kutyniok |
| 2022 | Graph Self-supervised Learning with Accurate Discrepancy Learning. Dongki Kim, Jinheon Baek, Sung Ju Hwang |
| 2022 | GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs. Zenan Li, Qitian Wu, Fan Nie, Junchi Yan |
| 2022 | GraphQNTK: Quantum Neural Tangent Kernel for Graph Data. Yehui Tang, Junchi Yan |
| 2022 | Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks. Arian R. Jamasb, Ramón Viñas Torné, Eric Ma, Yuanqi Du, Charles Harris, Kexin Huang, Dominic Hall, Pietro Lió, Tom L. Blundell |
| 2022 | Green Hierarchical Vision Transformer for Masked Image Modeling. Lang Huang, Shan You, Mingkai Zheng, Fei Wang, Chen Qian, Toshihiko Yamasaki |
| 2022 | GriddlyJS: A Web IDE for Reinforcement Learning. Christopher Bamford, Minqi Jiang, Mikayel Samvelyan, Tim Rocktäschel |
| 2022 | Grounded Reinforcement Learning: Learning to Win the Game under Human Commands. Shusheng Xu, Huaijie Wang, Yi Wu |
| 2022 | Grounded Video Situation Recognition. Zeeshan Khan, C. V. Jawahar, Makarand Tapaswi |
| 2022 | Grounding Aleatoric Uncertainty for Unsupervised Environment Design. Minqi Jiang, Michael Dennis, Jack Parker-Holder, Andrei Lupu, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel, Jakob N. Foerster |
| 2022 | Group Meritocratic Fairness in Linear Contextual Bandits. Riccardo Grazzi, Arya Akhavan, John Isak Texas Falk, Leonardo Cella, Massimiliano Pontil |
| 2022 | Grow and Merge: A Unified Framework for Continuous Categories Discovery. Xinwei Zhang, Jianwen Jiang, Yutong Feng, Zhi-Fan Wu, Xibin Zhao, Hai Wan, Mingqian Tang, Rong Jin, Yue Gao |
| 2022 | Guaranteed Conservation of Momentum for Learning Particle-based Fluid Dynamics. Lukas Prantl, Benjamin Ummenhofer, Vladlen Koltun, Nils Thuerey |
| 2022 | HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions. Lingjiao Chen, Zhihua Jin, Sabri Eyuboglu, Christopher Ré, Matei Zaharia, James Y. Zou |
| 2022 | HF-NeuS: Improved Surface Reconstruction Using High-Frequency Details. Yiqun Wang, Ivan Skorokhodov, Peter Wonka |
| 2022 | HSDF: Hybrid Sign and Distance Field for Modeling Surfaces with Arbitrary Topologies. Li Wang, Jie Yang, Weikai Chen, Xiaoxu Meng, Bo Yang, Jintao Li, Lin Gao |
| 2022 | HSurf-Net: Normal Estimation for 3D Point Clouds by Learning Hyper Surfaces. Qing Li, Yu-Shen Liu, Jin-San Cheng, Cheng Wang, Yi Fang, Zhizhong Han |
| 2022 | HUMANISE: Language-conditioned Human Motion Generation in 3D Scenes. Zan Wang, Yixin Chen, Tengyu Liu, Yixin Zhu, Wei Liang, Siyuan Huang |
| 2022 | HUMUS-Net: Hybrid Unrolled Multi-scale Network Architecture for Accelerated MRI Reconstruction. Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi |
| 2022 | HYPRO: A Hybridly Normalized Probabilistic Model for Long-Horizon Prediction of Event Sequences. Siqiao Xue, Xiaoming Shi, James Y. Zhang, Hongyuan Mei |
| 2022 | Hamiltonian Latent Operators for content and motion disentanglement in image sequences. Asif Khan, Amos J. Storkey |
| 2022 | Hand-Object Interaction Image Generation. Hezhen Hu, Weilun Wang, Wengang Zhou, Houqiang Li |
| 2022 | HandMeThat: Human-Robot Communication in Physical and Social Environments. Yanming Wan, Jiayuan Mao, Josh Tenenbaum |
| 2022 | Handcrafted Backdoors in Deep Neural Networks. Sanghyun Hong, Nicholas Carlini, Alexey Kurakin |
| 2022 | Hard ImageNet: Segmentations for Objects with Strong Spurious Cues. Mazda Moayeri, Sahil Singla, Soheil Feizi |
| 2022 | Hardness in Markov Decision Processes: Theory and Practice. Michelangelo Conserva, Paulo E. Rauber |
| 2022 | Hardness of Noise-Free Learning for Two-Hidden-Layer Neural Networks. Sitan Chen, Aravind Gollakota, Adam R. Klivans, Raghu Meka |
| 2022 | Harmonizing the object recognition strategies of deep neural networks with humans. Thomas Fel, Ivan F. Rodriguez Rodriguez, Drew Linsley, Thomas Serre |
| 2022 | Heatmap Distribution Matching for Human Pose Estimation. Haoxuan Qu, Li Xu, Yujun Cai, Lin Geng Foo, Jun Liu |
| 2022 | Hedging as Reward Augmentation in Probabilistic Graphical Models. Debarun Bhattacharjya, Radu Marinescu |
| 2022 | Heterogeneous Skill Learning for Multi-agent Tasks. Yuntao Liu, Yuan Li, Xinhai Xu, Yong Dou, Donghong Liu |
| 2022 | Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit. Boaz Barak, Benjamin L. Edelman, Surbhi Goel, Sham M. Kakade, Eran Malach, Cyril Zhang |
| 2022 | Hiding Images in Deep Probabilistic Models. Haoyu Chen, Linqi Song, Zhenxing Qian, Xinpeng Zhang, Kede Ma |
| 2022 | HierSpeech: Bridging the Gap between Text and Speech by Hierarchical Variational Inference using Self-supervised Representations for Speech Synthesis. Sang-Hoon Lee, Seung-Bin Kim, Ji-Hyun Lee, Eunwoo Song, Min-Jae Hwang, Seong-Whan Lee |
| 2022 | Hierarchical Agglomerative Graph Clustering in Poly-Logarithmic Depth. Laxman Dhulipala, David Eisenstat, Jakub Lacki, Vahab Mirrokni, Jessica Shi |
| 2022 | Hierarchical Channel-spatial Encoding for Communication-efficient Collaborative Learning. Qihua Zhou, Song Guo, Yi Liu, Jie Zhang, Jiewei Zhang, Tao Guo, Zhenda Xu, Xun Liu, Zhihao Qu |
| 2022 | Hierarchical Graph Transformer with Adaptive Node Sampling. Zaixi Zhang, Qi Liu, Qingyong Hu, Chee-Kong Lee |
| 2022 | Hierarchical Lattice Layer for Partially Monotone Neural Networks. Hiroki Yanagisawa, Kohei Miyaguchi, Takayuki Katsuki |
| 2022 | Hierarchical Normalization for Robust Monocular Depth Estimation. Chi Zhang, Wei Yin, Billzb Wang, Gang Yu, Bin Fu, Chunhua Shen |
| 2022 | Hierarchical classification at multiple operating points. Jack Valmadre |
| 2022 | High-Order Pooling for Graph Neural Networks with Tensor Decomposition. Chenqing Hua, Guillaume Rabusseau, Jian Tang |
| 2022 | High-dimensional Additive Gaussian Processes under Monotonicity Constraints. Andrés F. López-Lopera, François Bachoc, Olivier Roustant |
| 2022 | High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation. Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu, Greg Yang |
| 2022 | High-dimensional limit theorems for SGD: Effective dynamics and critical scaling. Gérard Ben Arous, Reza Gheissari, Aukosh Jagannath |
| 2022 | Hilbert Distillation for Cross-Dimensionality Networks. Dian Qin, Haishuai Wang, Zhe Liu, Hongjia Xu, Sheng Zhou, Jiajun Bu |
| 2022 | Holomorphic Equilibrium Propagation Computes Exact Gradients Through Finite Size Oscillations. Axel Laborieux, Friedemann Zenke |
| 2022 | Homomorphic Matrix Completion. Xiao-Yang Liu, Zechu (Steven) Li, Xiaodong Wang |
| 2022 | Honor of Kings Arena: an Environment for Generalization in Competitive Reinforcement Learning. Hua Wei, Jingxiao Chen, Xiyang Ji, Hongyang Qin, Minwen Deng, Siqin Li, Liang Wang, Weinan Zhang, Yong Yu, Liu Lin, Lanxiao Huang, Deheng Ye, Qiang Fu, Wei Yang |
| 2022 | HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions. Yongming Rao, Wenliang Zhao, Yansong Tang, Jie Zhou, Ser-Nam Lim, Jiwen Lu |
| 2022 | House of Cans: Covert Transmission of Internal Datasets via Capacity-Aware Neuron Steganography. Xudong Pan, Shengyao Zhang, Mi Zhang, Yifan Yan, Min Yang |
| 2022 | How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders. Qi Zhang, Yifei Wang, Yisen Wang |
| 2022 | How Powerful are K-hop Message Passing Graph Neural Networks. Jiarui Feng, Yixin Chen, Fuhai Li, Anindya Sarkar, Muhan Zhang |
| 2022 | How Sampling Impacts the Robustness of Stochastic Neural Networks. Sina Däubener, Asja Fischer |
| 2022 | How Transferable are Video Representations Based on Synthetic Data? Yo-whan Kim, Samarth Mishra, SouYoung Jin, Rameswar Panda, Hilde Kuehne, Leonid Karlinsky, Venkatesh Saligrama, Kate Saenko, Aude Oliva, Rogério Feris |
| 2022 | How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning? Chengxu Zhuang, Ziyu Xiang, Yoon Bai, Xiaoxuan Jia, Nicholas B. Turk-Browne, Kenneth A. Norman, James J. DiCarlo, Dan Yamins |
| 2022 | How Would The Viewer Feel? Estimating Wellbeing From Video Scenarios. Mantas Mazeika, Eric Tang, Andy Zou, Steven Basart, Jun Shern Chan, Dawn Song, David A. Forsyth, Jacob Steinhardt, Dan Hendrycks |
| 2022 | How and Why to Manipulate Your Own Agent: On the Incentives of Users of Learning Agents. Yoav Kolumbus, Noam Nisan |
| 2022 | How to talk so AI will learn: Instructions, descriptions, and autonomy. Theodore R. Sumers, Robert D. Hawkins, Mark K. Ho, Tom Griffiths, Dylan Hadfield-Menell |
| 2022 | Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models. Yang Shu, Zhangjie Cao, Ziyang Zhang, Jianmin Wang, Mingsheng Long |
| 2022 | Human-AI Collaborative Bayesian Optimisation. Arun Kumar A. V., Santu Rana, Alistair Shilton, Svetha Venkatesh |
| 2022 | Human-AI Shared Control via Policy Dissection. Quanyi Li, Zhenghao Peng, Haibin Wu, Lan Feng, Bolei Zhou |
| 2022 | Human-Robotic Prosthesis as Collaborating Agents for Symmetrical Walking. Ruofan Wu, Junmin Zhong, Brent Wallace, Xiang Gao, He Huang, Jennie Si |
| 2022 | HumanLiker: A Human-like Object Detector to Model the Manual Labeling Process. Haoran Wei, Ping Guo, Yangguang Zhu, Chenglong Liu, Peng Wang |
| 2022 | Hybrid Neural Autoencoders for Stimulus Encoding in Visual and Other Sensory Neuroprostheses. Jacob Granley, Lucas Relic, Michael Beyeler |
| 2022 | Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights. Konstantin Schürholt, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth |
| 2022 | HyperDomainNet: Universal Domain Adaptation for Generative Adversarial Networks. Aibek Alanov, Vadim Titov, Dmitry P. Vetrov |
| 2022 | HyperMiner: Topic Taxonomy Mining with Hyperbolic Embedding. Yishi Xu, Dongsheng Wang, Bo Chen, Ruiying Lu, Zhibin Duan, Mingyuan Zhou |
| 2022 | HyperTree Proof Search for Neural Theorem Proving. Guillaume Lample, Timothée Lacroix, Marie-Anne Lachaux, Aurélien Rodriguez, Amaury Hayat, Thibaut Lavril, Gabriel Ebner, Xavier Martinet |
| 2022 | Hyperbolic Embedding Inference for Structured Multi-Label Prediction. Bo Xiong, Michael Cochez, Mojtaba Nayyeri, Steffen Staab |
| 2022 | Hyperbolic Feature Augmentation via Distribution Estimation and Infinite Sampling on Manifolds. Zhi Gao, Yuwei Wu, Yunde Jia, Mehrtash Harandi |
| 2022 | Hyperparameter Sensitivity in Deep Outlier Detection: Analysis and a Scalable Hyper-Ensemble Solution. Xueying Ding, Lingxiao Zhao, Leman Akoglu |
| 2022 | Hypothesis Testing for Differentially Private Linear Regression. Daniel Alabi, Salil P. Vadhan |
| 2022 | I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classification. Muhammad Ferjad Naeem, Yongqin Xian, Luc Van Gool, Federico Tombari |
| 2022 | I2Q: A Fully Decentralized Q-Learning Algorithm. Jiechuan Jiang, Zongqing Lu |
| 2022 | IKEA-Manual: Seeing Shape Assembly Step by Step. Ruocheng Wang, Yunzhi Zhang, Jiayuan Mao, Ran Zhang, Chin-Yi Cheng, Jiajun Wu |
| 2022 | IM-Loss: Information Maximization Loss for Spiking Neural Networks. Yufei Guo, Yuanpei Chen, Liwen Zhang, Xiaode Liu, YingLei Wang, Xuhui Huang, Zhe Ma |
| 2022 | IMED-RL: Regret optimal learning of ergodic Markov decision processes. Fabien Pesquerel, Odalric-Ambrym Maillard |
| 2022 | INRAS: Implicit Neural Representation for Audio Scenes. Kun Su, Mingfei Chen, Eli Shlizerman |
| 2022 | Identifiability and generalizability from multiple experts in Inverse Reinforcement Learning. Paul Rolland, Luca Viano, Norman Schürhoff, Boris Nikolov, Volkan Cevher |
| 2022 | Identifiability of deep generative models without auxiliary information. Bohdan Kivva, Goutham Rajendran, Pradeep Ravikumar, Bryon Aragam |
| 2022 | Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy. Yi Liu, Ke Sun, Bei Jiang, Linglong Kong |
| 2022 | Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials. Eshaan Nichani, Yu Bai, Jason D. Lee |
| 2022 | If Influence Functions are the Answer, Then What is the Question? Juhan Bae, Nathan Ng, Alston Lo, Marzyeh Ghassemi, Roger B. Grosse |
| 2022 | Imbalance Trouble: Revisiting Neural-Collapse Geometry. Christos Thrampoulidis, Ganesh Ramachandra Kini, Vala Vakilian, Tina Behnia |
| 2022 | Imitating Past Successes can be Very Suboptimal. Benjamin Eysenbach, Soumith Udatha, Russ Salakhutdinov, Sergey Levine |
| 2022 | Implications of Model Indeterminacy for Explanations of Automated Decisions. Marc-Etienne Brunet, Ashton Anderson, Richard S. Zemel |
| 2022 | Implicit Bias of Gradient Descent on Reparametrized Models: On Equivalence to Mirror Descent. Zhiyuan Li, Tianhao Wang, Jason D. Lee, Sanjeev Arora |
| 2022 | Implicit Neural Representations with Levels-of-Experts. Zekun Hao, Arun Mallya, Serge J. Belongie, Ming-Yu Liu |
| 2022 | Implicit Regularization or Implicit Conditioning? Exact Risk Trajectories of SGD in High Dimensions. Courtney Paquette, Elliot Paquette, Ben Adlam, Jeffrey Pennington |
| 2022 | Implicit Warping for Animation with Image Sets. Arun Mallya, Ting-Chun Wang, Ming-Yu Liu |
| 2022 | Improved Algorithms for Neural Active Learning. Yikun Ban, Yuheng Zhang, Hanghang Tong, Arindam Banerjee, Jingrui He |
| 2022 | Improved Bounds on Neural Complexity for Representing Piecewise Linear Functions. Kuan-Lin Chen, Harinath Garudadri, Bhaskar D. Rao |
| 2022 | Improved Convergence Rate of Stochastic Gradient Langevin Dynamics with Variance Reduction and its Application to Optimization. Yuri Kinoshita, Taiji Suzuki |
| 2022 | Improved Coresets for Euclidean k-Means. Vincent Cohen-Addad, Kasper Green Larsen, David Saulpic, Chris Schwiegelshohn, Omar Ali Sheikh-Omar |
| 2022 | Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams. Sergey Denisov, H. Brendan McMahan, John Rush, Adam D. Smith, Abhradeep Guha Thakurta |
| 2022 | Improved Feature Distillation via Projector Ensemble. Yudong Chen, Sen Wang, Jiajun Liu, Xuwei Xu, Frank de Hoog, Zi Huang |
| 2022 | Improved Fine-Tuning by Better Leveraging Pre-Training Data. Ziquan Liu, Yi Xu, Yuanhong Xu, Qi Qian, Hao Li, Xiangyang Ji, Antoni B. Chan, Rong Jin |
| 2022 | Improved Imaging by Invex Regularizers with Global Optima Guarantees. Samuel Pinilla, Tingting Mu, Neil Bourne, Jeyan Thiyagalingam |
| 2022 | Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs. Yeoneung Kim, Insoon Yang, Kwang-Sung Jun |
| 2022 | Improved Utility Analysis of Private CountSketch. Rasmus Pagh, Mikkel Thorup |
| 2022 | Improved techniques for deterministic l2 robustness. Sahil Singla, Soheil Feizi |
| 2022 | Improving 3D-aware Image Synthesis with A Geometry-aware Discriminator. Zifan Shi, Yinghao Xu, Yujun Shen, Deli Zhao, Qifeng Chen, Dit-Yan Yeung |
| 2022 | Improving Barely Supervised Learning by Discriminating Unlabeled Samples with Super-Class. Guan Gui, Zhen Zhao, Lei Qi, Luping Zhou, Lei Wang, Yinghuan Shi |
| 2022 | Improving Certified Robustness via Statistical Learning with Logical Reasoning. Zhuolin Yang, Zhikuan Zhao, Boxin Wang, Jiawei Zhang, Linyi Li, Hengzhi Pei, Bojan Karlas, Ji Liu, Heng Guo, Ce Zhang, Bo Li |
| 2022 | Improving Diffusion Models for Inverse Problems using Manifold Constraints. Hyungjin Chung, Byeongsu Sim, Dohoon Ryu, Jong Chul Ye |
| 2022 | Improving GANs with A Dynamic Discriminator. Ceyuan Yang, Yujun Shen, Yinghao Xu, Deli Zhao, Bo Dai, Bolei Zhou |
| 2022 | Improving Generative Adversarial Networks via Adversarial Learning in Latent Space. Yang Li, Yichuan Mo, Liangliang Shi, Junchi Yan |
| 2022 | Improving Intrinsic Exploration with Language Abstractions. Jesse Mu, Victor Zhong, Roberta Raileanu, Minqi Jiang, Noah D. Goodman, Tim Rocktäschel, Edward Grefenstette |
| 2022 | Improving Multi-Task Generalization via Regularizing Spurious Correlation. Ziniu Hu, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong, Yizhou Sun, Ed H. Chi |
| 2022 | Improving Neural Ordinary Differential Equations with Nesterov's Accelerated Gradient Method. Ho Huu Nghia Nguyen, Tan Nguyen, Huyen Vo, Stanley J. Osher, Thieu Vo |
| 2022 | Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors. Qixun Wang, Yifei Wang, Hong Zhu, Yisen Wang |
| 2022 | Improving Policy Learning via Language Dynamics Distillation. Victor Zhong, Jesse Mu, Luke Zettlemoyer, Edward Grefenstette, Tim Rocktäschel |
| 2022 | Improving Self-Supervised Learning by Characterizing Idealized Representations. Yann Dubois, Stefano Ermon, Tatsunori B. Hashimoto, Percy Liang |
| 2022 | Improving Task-Specific Generalization in Few-Shot Learning via Adaptive Vicinal Risk Minimization. Long-Kai Huang, Ying Wei |
| 2022 | Improving Transformer with an Admixture of Attention Heads. Tan Nguyen, Tam Nguyen, Hai Do, Khai Nguyen, Vishwanath Saragadam, Minh Pham, Duy Khuong Nguyen, Nhat Ho, Stanley J. Osher |
| 2022 | Improving Variational Autoencoders with Density Gap-based Regularization. Jianfei Zhang, Jun Bai, Chenghua Lin, Yanmeng Wang, Wenge Rong |
| 2022 | Improving Zero-Shot Generalization in Offline Reinforcement Learning using Generalized Similarity Functions. Bogdan Mazoure, Ilya Kostrikov, Ofir Nachum, Jonathan Tompson |
| 2022 | In Defense of the Unitary Scalarization for Deep Multi-Task Learning. Vitaly Kurin, Alessandro De Palma, Ilya Kostrikov, Shimon Whiteson, Pawan Kumar Mudigonda |
| 2022 | In Differential Privacy, There is Truth: on Vote-Histogram Leakage in Ensemble Private Learning. Jiaqi Wang, Roei Schuster, Ilia Shumailov, David Lie, Nicolas Papernot |
| 2022 | In What Ways Are Deep Neural Networks Invariant and How Should We Measure This? Henry Kvinge, Tegan Emerson, Grayson Jorgenson, Scott Vasquez, Tim Doster, Jesse D. Lew |
| 2022 | In the Eye of the Beholder: Robust Prediction with Causal User Modeling. Amir Feder, Guy Horowitz, Yoav Wald, Roi Reichart, Nir Rosenfeld |
| 2022 | Incentivizing Combinatorial Bandit Exploration. Xinyan Hu, Dung Daniel T. Ngo, Aleksandrs Slivkins, Zhiwei Steven Wu |
| 2022 | Inception Transformer. Chenyang Si, Weihao Yu, Pan Zhou, Yichen Zhou, Xinchao Wang, Shuicheng Yan |
| 2022 | Incorporating Bias-aware Margins into Contrastive Loss for Collaborative Filtering. An Zhang, Wenchang Ma, Xiang Wang, Tat-Seng Chua |
| 2022 | Increasing Confidence in Adversarial Robustness Evaluations. Roland S. Zimmermann, Wieland Brendel, Florian Tramèr, Nicholas Carlini |
| 2022 | Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces. Leonard Papenmeier, Luigi Nardi, Matthias Poloczek |
| 2022 | Incrementality Bidding via Reinforcement Learning under Mixed and Delayed Rewards. Ashwinkumar Badanidiyuru Varadaraja, Zhe Feng, Tianxi Li, Haifeng Xu |
| 2022 | Independence Testing for Bounded Degree Bayesian Networks. Arnab Bhattacharyya, Clément L. Canonne, Joy Qiping Yang |
| 2022 | Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models. Haoyue Dai, Peter Spirtes, Kun Zhang |
| 2022 | Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples. Maura Pintor, Luca Demetrio, Angelo Sotgiu, Ambra Demontis, Nicholas Carlini, Battista Biggio, Fabio Roli |
| 2022 | Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence. Boyi Liu, Jiayang Li, Zhuoran Yang, Hoi-To Wai, Mingyi Hong, Yu Marco Nie, Zhaoran Wang |
| 2022 | Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network? Yibo Yang, Shixiang Chen, Xiangtai Li, Liang Xie, Zhouchen Lin, Dacheng Tao |
| 2022 | Inductive Logical Query Answering in Knowledge Graphs. Michael Galkin, Zhaocheng Zhu, Hongyu Ren, Jian Tang |
| 2022 | Inference and Sampling for Archimax Copulas. Yuting Ng, Ali Hasan, Vahid Tarokh |
| 2022 | Infinite Recommendation Networks: A Data-Centric Approach. Noveen Sachdeva, Mehak Preet Dhaliwal, Carole-Jean Wu, Julian J. McAuley |
| 2022 | Infinite-Fidelity Coregionalization for Physical Simulation. Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe |
| 2022 | Influencing Long-Term Behavior in Multiagent Reinforcement Learning. Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster, Michael Everett, Chuangchuang Sun, Gerald Tesauro, Jonathan P. How |
| 2022 | Information bottleneck theory of high-dimensional regression: relevancy, efficiency and optimality. Vudtiwat Ngampruetikorn, David J. Schwab |
| 2022 | Information-Theoretic GAN Compression with Variational Energy-based Model. Minsoo Kang, Hyewon Yoo, Eunhee Kang, Sehwan Ki, Hyong-Euk Lee, Bohyung Han |
| 2022 | Information-Theoretic Safe Exploration with Gaussian Processes. Alessandro G. Bottero, Carlos E. Luis, Julia Vinogradska, Felix Berkenkamp, Jan Peters |
| 2022 | Inherently Explainable Reinforcement Learning in Natural Language. Xiangyu Peng, Mark O. Riedl, Prithviraj Ammanabrolu |
| 2022 | Injecting Domain Knowledge from Empirical Interatomic Potentials to Neural Networks for Predicting Material Properties. Zeren Shui, Daniel S. Karls, Mingjian Wen, Ilia A. Nikiforov, Ellad B. Tadmor, George Karypis |
| 2022 | InsNet: An Efficient, Flexible, and Performant Insertion-based Text Generation Model. Sidi Lu, Tao Meng, Nanyun Peng |
| 2022 | InsPro: Propagating Instance Query and Proposal for Online Video Instance Segmentation. Fei He, Haoyang Zhang, Naiyu Gao, Jian Jia, Yanhu Shan, Xin Zhao, Kaiqi Huang |
| 2022 | Insights into Pre-training via Simpler Synthetic Tasks. Yuhuai Wu, Felix Li, Percy Liang |
| 2022 | Instability and Local Minima in GAN Training with Kernel Discriminators. Evan Becker, Parthe Pandit, Sundeep Rangan, Alyson K. Fletcher |
| 2022 | Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees. Jonathan Brophy, Daniel Lowd |
| 2022 | Instance-Dependent Near-Optimal Policy Identification in Linear MDPs via Online Experiment Design. Andrew Wagenmaker, Kevin Jamieson |
| 2022 | Instance-based Learning for Knowledge Base Completion. Wanyun Cui, Xingran Chen |
| 2022 | Instance-optimal PAC Algorithms for Contextual Bandits. Zhaoqi Li, Lillian J. Ratliff, Houssam Nassif, Kevin Jamieson, Lalit Jain |
| 2022 | Integral Probability Metrics PAC-Bayes Bounds. Ron Amit, Baruch Epstein, Shay Moran, Ron Meir |
| 2022 | Interaction Modeling with Multiplex Attention. Fan-Yun Sun, Isaac Kauvar, Ruohan Zhang, Jiachen Li, Mykel J. Kochenderfer, Jiajun Wu, Nick Haber |
| 2022 | Interaction-Grounded Learning with Action-Inclusive Feedback. Tengyang Xie, Akanksha Saran, Dylan J. Foster, Lekan P. Molu, Ida Momennejad, Nan Jiang, Paul Mineiro, John Langford |
| 2022 | Intermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation. Yuanwei Liu, Nian Liu, Xiwen Yao, Junwei Han |
| 2022 | Interpolation and Regularization for Causal Learning. Leena Chennuru Vankadara, Luca Rendsburg, Ulrike von Luxburg, Debarghya Ghoshdastidar |
| 2022 | Interpreting Operation Selection in Differentiable Architecture Search: A Perspective from Influence-Directed Explanations. Miao Zhang, Wei Huang, Bin Yang |
| 2022 | Interventions, Where and How? Experimental Design for Causal Models at Scale. Panagiotis Tigas, Yashas Annadani, Andrew Jesson, Bernhard Schölkopf, Yarin Gal, Stefan Bauer |
| 2022 | Intra-agent speech permits zero-shot task acquisition. Chen Yan, Federico Carnevale, Petko Georgiev, Adam Santoro, Aurelia Guy, Alistair Muldal, Chia-Chun Hung, Josh Abramson, Timothy P. Lillicrap, Gregory Wayne |
| 2022 | Intrinsic dimensionality estimation using Normalizing Flows. Christian Horvat, Jean-Pascal Pfister |
| 2022 | Introspective Learning : A Two-Stage approach for Inference in Neural Networks. Mohit Prabhushankar, Ghassan AlRegib |
| 2022 | Invariance Learning based on Label Hierarchy. Shoji Toyota, Kenji Fukumizu |
| 2022 | Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations. Alexander Immer, Tycho F. A. van der Ouderaa, Gunnar Rätsch, Vincent Fortuin, Mark van der Wilk |
| 2022 | Invariance-Aware Randomized Smoothing Certificates. Jan Schuchardt, Stephan Günnemann |
| 2022 | Invariant and Transportable Representations for Anti-Causal Domain Shifts. Yibo Jiang, Victor Veitch |
| 2022 | Inverse Design for Fluid-Structure Interactions using Graph Network Simulators. Kelsey R. Allen, Tatiana Lopez-Guevara, Kimberly L. Stachenfeld, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Jessica B. Hamrick, Tobias Pfaff |
| 2022 | Inverse Game Theory for Stackelberg Games: the Blessing of Bounded Rationality. Jibang Wu, Weiran Shen, Fei Fang, Haifeng Xu |
| 2022 | Invertible Monotone Operators for Normalizing Flows. Byeongkeun Ahn, Chiyoon Kim, Youngjoon Hong, Hyunwoo J. Kim |
| 2022 | Iron: Private Inference on Transformers. Meng Hao, Hongwei Li, Hanxiao Chen, Pengzhi Xing, Guowen Xu, Tianwei Zhang |
| 2022 | Is $L^2$ Physics Informed Loss Always Suitable for Training Physics Informed Neural Network? Chuwei Wang, Shanda Li, Di He, Liwei Wang |
| 2022 | Is Integer Arithmetic Enough for Deep Learning Training? Alireza Ghaffari, Marzieh S. Tahaei, Mohammadreza Tayaranian, Masoud Asgharian, Vahid Partovi Nia |
| 2022 | Is Out-of-Distribution Detection Learnable? Zhen Fang, Yixuan Li, Jie Lu, Jiahua Dong, Bo Han, Feng Liu |
| 2022 | Is Sortition Both Representative and Fair? Soroush Ebadian, Gregory Kehne, Evi Micha, Ariel D. Procaccia, Nisarg Shah |
| 2022 | Is a Modular Architecture Enough? Sarthak Mittal, Yoshua Bengio, Guillaume Lajoie |
| 2022 | Is one annotation enough? - A data-centric image classification benchmark for noisy and ambiguous label estimation. Lars Schmarje, Vasco Grossmann, Claudius Zelenka, Sabine Dippel, Rainer Kiko, Mariusz Oszust, Matti Pastell, Jenny Stracke, Anna Valros, Nina Volkmann, Reinhard Koch |
| 2022 | Is this the Right Neighborhood? Accurate and Query Efficient Model Agnostic Explanations. Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Karthikeyan Shanmugam |
| 2022 | Iso-Dream: Isolating and Leveraging Noncontrollable Visual Dynamics in World Models. Minting Pan, Xiangming Zhu, Yunbo Wang, Xiaokang Yang |
| 2022 | Isometric 3D Adversarial Examples in the Physical World. Yibo Miao, Yinpeng Dong, Jun Zhu, Xiao-Shan Gao |
| 2022 | Iterative Feature Matching: Toward Provable Domain Generalization with Logarithmic Environments. Yining Chen, Elan Rosenfeld, Mark Sellke, Tengyu Ma, Andrej Risteski |
| 2022 | Iterative Scene Graph Generation. Siddhesh Khandelwal, Leonid Sigal |
| 2022 | Iterative Structural Inference of Directed Graphs. Aoran Wang, Jun Pang |
| 2022 | JAHS-Bench-201: A Foundation For Research On Joint Architecture And Hyperparameter Search. Archit Bansal, Danny Stoll, Maciej Janowski, Arber Zela, Frank Hutter |
| 2022 | JAWS: Auditing Predictive Uncertainty Under Covariate Shift. Drew Prinster, Anqi Liu, Suchi Saria |
| 2022 | Joint Entropy Search For Maximally-Informed Bayesian Optimization. Carl Hvarfner, Frank Hutter, Luigi Nardi |
| 2022 | Joint Entropy Search for Multi-Objective Bayesian Optimization. Ben Tu, Axel Gandy, Nikolas Kantas, Behrang Shafei |
| 2022 | Joint Learning of 2D-3D Weakly Supervised Semantic Segmentation. Hyeokjun Kweon, Kuk-Jin Yoon |
| 2022 | Jump Self-attention: Capturing High-order Statistics in Transformers. Haoyi Zhou, Siyang Xiao, Shanghang Zhang, Jieqi Peng, Shuai Zhang, Jianxin Li |
| 2022 | K-LITE: Learning Transferable Visual Models with External Knowledge. Sheng Shen, Chunyuan Li, Xiaowei Hu, Yujia Xie, Jianwei Yang, Pengchuan Zhang, Zhe Gan, Lijuan Wang, Lu Yuan, Ce Liu, Kurt Keutzer, Trevor Darrell, Anna Rohrbach, Jianfeng Gao |
| 2022 | K-Radar: 4D Radar Object Detection for Autonomous Driving in Various Weather Conditions. Dong-Hee Paek, Seung-Hyun Kong, Kevin Tirta Wijaya |
| 2022 | KERPLE: Kernelized Relative Positional Embedding for Length Extrapolation. Ta-Chung Chi, Ting-Han Fan, Peter J. Ramadge, Alexander Rudnicky |
| 2022 | KSD Aggregated Goodness-of-fit Test. Antonin Schrab, Benjamin Guedj, Arthur Gretton |
| 2022 | Kantorovich Strikes Back! Wasserstein GANs are not Optimal Transport? Alexander Korotin, Alexander Kolesov, Evgeny Burnaev |
| 2022 | Kernel Interpolation with Sparse Grids. Mohit Yadav, Daniel R. Sheldon, Cameron Musco |
| 2022 | Kernel Memory Networks: A Unifying Framework for Memory Modeling. Georgios Iatropoulos, Johanni Brea, Wulfram Gerstner |
| 2022 | Kernel Multimodal Continuous Attention. Alexander Moreno, Zhenke Wu, Supriya Nagesh, Walter H. Dempsey, James M. Rehg |
| 2022 | Kernel similarity matching with Hebbian networks. Kyle Luther, H. Sebastian Seung |
| 2022 | Keypoint-Guided Optimal Transport with Applications in Heterogeneous Domain Adaptation. Xiang Gu, Yucheng Yang, Wei Zeng, Jian Sun, Zongben Xu |
| 2022 | Knowledge Distillation Improves Graph Structure Augmentation for Graph Neural Networks. Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li |
| 2022 | Knowledge Distillation from A Stronger Teacher. Tao Huang, Shan You, Fei Wang, Chen Qian, Chang Xu |
| 2022 | Knowledge Distillation: Bad Models Can Be Good Role Models. Gal Kaplun, Eran Malach, Preetum Nakkiran, Shai Shalev-Shwartz |
| 2022 | Knowledge-Aware Bayesian Deep Topic Model. Dongsheng Wang, Yishi Xu, Miaoge Li, Zhibin Duan, Chaojie Wang, Bo Chen, Mingyuan Zhou |
| 2022 | LAION-5B: An open large-scale dataset for training next generation image-text models. Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, Jenia Jitsev |
| 2022 | LAMP: Extracting Text from Gradients with Language Model Priors. Mislav Balunovic, Dimitar I. Dimitrov, Nikola Jovanovic, Martin T. Vechev |
| 2022 | LAPO: Latent-Variable Advantage-Weighted Policy Optimization for Offline Reinforcement Learning. Xi Chen, Ali Ghadirzadeh, Tianhe Yu, Jianhao Wang, Alex Yuan Gao, Wenzhe Li, Liang Bin, Chelsea Finn, Chongjie Zhang |
| 2022 | LASSIE: Learning Articulated Shapes from Sparse Image Ensemble via 3D Part Discovery. Chun-Han Yao, Wei-Chih Hung, Yuanzhen Li, Michael Rubinstein, Ming-Hsuan Yang, Varun Jampani |
| 2022 | LBD: Decouple Relevance and Observation for Individual-Level Unbiased Learning to Rank. Mouxiang Chen, Chenghao Liu, Zemin Liu, Jianling Sun |
| 2022 | LDSA: Learning Dynamic Subtask Assignment in Cooperative Multi-Agent Reinforcement Learning. Mingyu Yang, Jian Zhao, Xunhan Hu, Wengang Zhou, Jiangcheng Zhu, Houqiang Li |
| 2022 | LECO: Learnable Episodic Count for Task-Specific Intrinsic Reward. DaeJin Jo, Sungwoong Kim, Daniel Wontae Nam, Taehwan Kwon, Seungeun Rho, Jongmin Kim, Donghoon Lee |
| 2022 | LGDN: Language-Guided Denoising Network for Video-Language Modeling. Haoyu Lu, Mingyu Ding, Nanyi Fei, Yuqi Huo, Zhiwu Lu |
| 2022 | LIFT: Language-Interfaced Fine-Tuning for Non-language Machine Learning Tasks. Tuan Dinh, Yuchen Zeng, Ruisu Zhang, Ziqian Lin, Michael Gira, Shashank Rajput, Jy-yong Sohn, Dimitris S. Papailiopoulos, Kangwook Lee |
| 2022 | LION: Latent Point Diffusion Models for 3D Shape Generation. Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, Karsten Kreis |
| 2022 | LIPS - Learning Industrial Physical Simulation benchmark suite. Milad Leyli-Abadi, Antoine Marot, Jérôme Picault, David Danan, Mouadh Yagoubi, Benjamin Donnot, Seif Attoui, Pavel Dimitrov, Asma Farjallah, Clement Etienam |
| 2022 | LISA: Learning Interpretable Skill Abstractions from Language. Divyansh Garg, Skanda Vaidyanath, Kuno Kim, Jiaming Song, Stefano Ermon |
| 2022 | LOG: Active Model Adaptation for Label-Efficient OOD Generalization. Jie-Jing Shao, Lan-Zhe Guo, Xiaowen Yang, Yufeng Li |
| 2022 | LOT: Layer-wise Orthogonal Training on Improving l2 Certified Robustness. Xiaojun Xu, Linyi Li, Bo Li |
| 2022 | LST: Ladder Side-Tuning for Parameter and Memory Efficient Transfer Learning. Yi-Lin Sung, Jaemin Cho, Mohit Bansal |
| 2022 | LTMD: Learning Improvement of Spiking Neural Networks with Learnable Thresholding Neurons and Moderate Dropout. Siqi Wang, Tee Hiang Cheng, Meng-Hiot Lim |
| 2022 | Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting. Chengyu Dong, Liyuan Liu, Jingbo Shang |
| 2022 | Label-Aware Global Consistency for Multi-Label Learning with Single Positive Labels. Ming-Kun Xie, Jiahao Xiao, Sheng-Jun Huang |
| 2022 | Label-invariant Augmentation for Semi-Supervised Graph Classification. Han Yue, Chunhui Zhang, Chuxu Zhang, Hongfu Liu |
| 2022 | Langevin Autoencoders for Learning Deep Latent Variable Models. Shohei Taniguchi, Yusuke Iwasawa, Wataru Kumagai, Yutaka Matsuo |
| 2022 | Language Conditioned Spatial Relation Reasoning for 3D Object Grounding. Shizhe Chen, Pierre-Louis Guhur, Makarand Tapaswi, Cordelia Schmid, Ivan Laptev |
| 2022 | Language Models with Image Descriptors are Strong Few-Shot Video-Language Learners. Zhenhailong Wang, Manling Li, Ruochen Xu, Luowei Zhou, Jie Lei, Xudong Lin, Shuohang Wang, Ziyi Yang, Chenguang Zhu, Derek Hoiem, Shih-Fu Chang, Mohit Bansal, Heng Ji |
| 2022 | Laplacian Autoencoders for Learning Stochastic Representations. Marco Miani, Frederik Warburg, Pablo Moreno-Muñoz, Nicki Skafte Detlefsen, Søren Hauberg |
| 2022 | Large Language Models are Zero-Shot Reasoners. Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, Yusuke Iwasawa |
| 2022 | Large-Scale Differentiable Causal Discovery of Factor Graphs. Romain Lopez, Jan-Christian Hütter, Jonathan K. Pritchard, Aviv Regev |
| 2022 | Large-Scale Retrieval for Reinforcement Learning. Peter Conway Humphreys, Arthur Guez, Olivier Tieleman, Laurent Sifre, Theophane Weber, Timothy P. Lillicrap |
| 2022 | Large-batch Optimization for Dense Visual Predictions: Training Faster R-CNN in 4.2 Minutes. Zeyue Xue, Jianming Liang, Guanglu Song, Zhuofan Zong, Liang Chen, Yu Liu, Ping Luo |
| 2022 | Large-scale Optimization of Partial AUC in a Range of False Positive Rates. Yao Yao, Qihang Lin, Tianbao Yang |
| 2022 | LasUIE: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Model. Hao Fei, Shengqiong Wu, Jingye Li, Bobo Li, Fei Li, Libo Qin, Meishan Zhang, Min Zhang, Tat-Seng Chua |
| 2022 | Last-Iterate Convergence of Optimistic Gradient Method for Monotone Variational Inequalities. Eduard Gorbunov, Adrien B. Taylor, Gauthier Gidel |
| 2022 | Latency-aware Spatial-wise Dynamic Networks. Yizeng Han, Zhihang Yuan, Yifan Pu, Chenhao Xue, Shiji Song, Guangyu Sun, Gao Huang |
| 2022 | Latent Hierarchical Causal Structure Discovery with Rank Constraints. Biwei Huang, Charles Jia Han Low, Feng Xie, Clark Glymour, Kun Zhang |
| 2022 | Latent Planning via Expansive Tree Search. Robert Gieselmann, Florian T. Pokorny |
| 2022 | Layer Freezing & Data Sieving: Missing Pieces of a Generic Framework for Sparse Training. Geng Yuan, Yanyu Li, Sheng Li, Zhenglun Kong, Sergey Tulyakov, Xulong Tang, Yanzhi Wang, Jian Ren |
| 2022 | Lazy and Fast Greedy MAP Inference for Determinantal Point Process. Shinichi Hemmi, Taihei Oki, Shinsaku Sakaue, Kaito Fujii, Satoru Iwata |
| 2022 | Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering. Pan Lu, Swaroop Mishra, Tanglin Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, Ashwin Kalyan |
| 2022 | Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets. Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang |
| 2022 | Learn what matters: cross-domain imitation learning with task-relevant embeddings. Tim Franzmeyer, Philip H. S. Torr, João F. Henriques |
| 2022 | Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional Networks. Renan A. Rojas-Gomez, Teck-Yian Lim, Alexander G. Schwing, Minh N. Do, Raymond A. Yeh |
| 2022 | Learning (Very) Simple Generative Models Is Hard. Sitan Chen, Jerry Li, Yuanzhi Li |
| 2022 | Learning Active Camera for Multi-Object Navigation. Peihao Chen, Dongyu Ji, Kunyang Lin, Weiwen Hu, Wenbing Huang, Thomas H. Li, Mingkui Tan, Chuang Gan |
| 2022 | Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network. Ravinder Bhattoo, Sayan Ranu, N. M. Anoop Krishnan |
| 2022 | Learning Audio-Visual Dynamics Using Scene Graphs for Audio Source Separation. Moitreya Chatterjee, Narendra Ahuja, Anoop Cherian |
| 2022 | Learning Best Combination for Efficient N: M Sparsity. Yuxin Zhang, Mingbao Lin, Zhihang Lin, Yiting Luo, Ke Li, Fei Chao, Yongjian Wu, Rongrong Ji |
| 2022 | Learning Bipartite Graphs: Heavy Tails and Multiple Components. José Vinícius de Miranda Cardoso, Jiaxi Ying, Daniel P. Palomar |
| 2022 | Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs. Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng |
| 2022 | Learning Chaotic Dynamics in Dissipative Systems. Zongyi Li, Miguel Liu-Schiaffini, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew M. Stuart, Anima Anandkumar |
| 2022 | Learning Concept Credible Models for Mitigating Shortcuts. Jiaxuan Wang, Sarah Jabbour, Maggie Makar, Michael W. Sjoding, Jenna Wiens |
| 2022 | Learning Consistency-Aware Unsigned Distance Functions Progressively from Raw Point Clouds. Junsheng Zhou, Baorui Ma, Yu-Shen Liu, Yi Fang, Zhizhong Han |
| 2022 | Learning Contrastive Embedding in Low-Dimensional Space. Shuo Chen, Chen Gong, Jun Li, Jian Yang, Gang Niu, Masashi Sugiyama |
| 2022 | Learning Debiased Classifier with Biased Committee. Nayeong Kim, Sehyun Hwang, Sungsoo Ahn, Jaesik Park, Suha Kwak |
| 2022 | Learning Deep Input-Output Stable Dynamics. Ryosuke Kojima, Yuji Okamoto |
| 2022 | Learning Dense Object Descriptors from Multiple Views for Low-shot Category Generalization. Stefan Stojanov, Anh Thai, Zixuan Huang, James M. Rehg |
| 2022 | Learning Distinct and Representative Modes for Image Captioning. Qi Chen, Chaorui Deng, Qi Wu |
| 2022 | Learning Distributed and Fair Policies for Network Load Balancing as Markov Potential Game. Zhiyuan Yao, Zihan Ding |
| 2022 | Learning Distributions Generated by Single-Layer ReLU Networks in the Presence of Arbitrary Outliers. Saikiran Bulusu, Geethu Joseph, Mustafa Cenk Gursoy, Pramod K. Varshney |
| 2022 | Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces. Vladimir Kostic, Pietro Novelli, Andreas Maurer, Carlo Ciliberto, Lorenzo Rosasco, Massimiliano Pontil |
| 2022 | Learning Efficient Vision Transformers via Fine-Grained Manifold Distillation. Zhiwei Hao, Jianyuan Guo, Ding Jia, Kai Han, Yehui Tang, Chao Zhang, Han Hu, Yunhe Wang |
| 2022 | Learning Energy Networks with Generalized Fenchel-Young Losses. Mathieu Blondel, Felipe Llinares-López, Robert Dadashi, Léonard Hussenot, Matthieu Geist |
| 2022 | Learning Enhanced Representation for Tabular Data via Neighborhood Propagation. Kounianhua Du, Weinan Zhang, Ruiwen Zhou, Yangkun Wang, Xilong Zhao, Jiarui Jin, Quan Gan, Zheng Zhang, David P. Wipf |
| 2022 | Learning Equivariant Segmentation with Instance-Unique Querying. Wenguan Wang, James Liang, Dongfang Liu |
| 2022 | Learning Expressive Meta-Representations with Mixture of Expert Neural Processes. Qi Wang, Herke van Hoof |
| 2022 | Learning Fractional White Noises in Neural Stochastic Differential Equations. Anh Tong, Thanh Nguyen-Tang, Toan M. Tran, Jaesik Choi |
| 2022 | Learning General World Models in a Handful of Reward-Free Deployments. Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip J. Ball, Oleh Rybkin, Stephen Roberts, Tim Rocktäschel, Edward Grefenstette |
| 2022 | Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillation. Jieyi Bi, Yining Ma, Jiahai Wang, Zhiguang Cao, Jinbiao Chen, Yuan Sun, Yeow Meng Chee |
| 2022 | Learning Generalizable Part-based Feature Representation for 3D Point Clouds. Xin Wei, Xiang Gu, Jian Sun |
| 2022 | Learning Generalized Policy Automata for Relational Stochastic Shortest Path Problems. Rushang Karia, Rashmeet Kaur Nayyar, Siddharth Srivastava |
| 2022 | Learning Graph-embedded Key-event Back-tracing for Object Tracking in Event Clouds. Zhiyu Zhu, Junhui Hou, Xianqiang Lyu |
| 2022 | Learning Individualized Treatment Rules with Many Treatments: A Supervised Clustering Approach Using Adaptive Fusion. Haixu Ma, Donglin Zeng, Yufeng Liu |
| 2022 | Learning Infinite-Horizon Average-Reward Restless Multi-Action Bandits via Index Awareness. Guojun Xiong, Shufan Wang, Jian Li |
| 2022 | Learning Interface Conditions in Domain Decomposition Solvers. Ali Taghibakhshi, Nicolas Nytko, Tareq Uz Zaman, Scott P. MacLachlan, Luke N. Olson, Matthew West |
| 2022 | Learning Invariant Graph Representations for Out-of-Distribution Generalization. Haoyang Li, Ziwei Zhang, Xin Wang, Wenwu Zhu |
| 2022 | Learning Latent Seasonal-Trend Representations for Time Series Forecasting. Zhiyuan Wang, Xovee Xu, Weifeng Zhang, Goce Trajcevski, Ting Zhong, Fan Zhou |
| 2022 | Learning Long-Term Crop Management Strategies with CyclesGym. Matteo Turchetta, Luca Corinzia, Scott Sussex, Amanda Burton, Juan Herrera, Ioannis N. Athanasiadis, Joachim M. Buhmann, Andreas Krause |
| 2022 | Learning Manifold Dimensions with Conditional Variational Autoencoders. Yijia Zheng, Tong He, Yixuan Qiu, David P. Wipf |
| 2022 | Learning Mixed Multinomial Logits with Provable Guarantees. Yiqun Hu, David Simchi-Levi, Zhenzhen Yan |
| 2022 | Learning Modular Simulations for Homogeneous Systems. Jayesh K. Gupta, Sai Vemprala, Ashish Kapoor |
| 2022 | Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape Matching. Lei Li, Nicolas Donati, Maks Ovsjanikov |
| 2022 | Learning NP-Hard Multi-Agent Assignment Planning using GNN: Inference on a Random Graph and Provable Auction-Fitted Q-learning. Hyunwook Kang, Taehwan Kwon, Jinkyoo Park, James R. Morrison |
| 2022 | Learning Neural Acoustic Fields. Andrew F. Luo, Yilun Du, Michael J. Tarr, Josh Tenenbaum, Antonio Torralba, Chuang Gan |
| 2022 | Learning Neural Set Functions Under the Optimal Subset Oracle. Zijing Ou, Tingyang Xu, Qinliang Su, Yingzhen Li, Peilin Zhao, Yatao Bian |
| 2022 | Learning Optical Flow from Continuous Spike Streams. Rui Zhao, Ruiqin Xiong, Jing Zhao, Zhaofei Yu, Xiaopeng Fan, Tiejun Huang |
| 2022 | Learning Optimal Flows for Non-Equilibrium Importance Sampling. Yu Cao, Eric Vanden-Eijnden |
| 2022 | Learning Options via Compression. Yiding Jiang, Evan Zheran Liu, Benjamin Eysenbach, J. Zico Kolter, Chelsea Finn |
| 2022 | Learning Partial Equivariances From Data. David W. Romero, Suhas Lohit |
| 2022 | Learning Physical Dynamics with Subequivariant Graph Neural Networks. Jiaqi Han, Wenbing Huang, Hengbo Ma, Jiachen Li, Josh Tenenbaum, Chuang Gan |
| 2022 | Learning Physics Constrained Dynamics Using Autoencoders. Tsung-Yen Yang, Justinian Rosca, Karthik Narasimhan, Peter J. Ramadge |
| 2022 | Learning Predictions for Algorithms with Predictions. Misha Khodak, Maria-Florina Balcan, Ameet Talwalkar, Sergei Vassilvitskii |
| 2022 | Learning Probabilistic Models from Generator Latent Spaces with Hat EBM. Mitch Hill, Erik Nijkamp, Jonathan Mitchell, Bo Pang, Song-Chun Zhu |
| 2022 | Learning Recourse on Instance Environment to Enhance Prediction Accuracy. Lokesh Nagalapatti, Guntakanti Sai Koushik, Abir De, Sunita Sarawagi |
| 2022 | Learning Representations via a Robust Behavioral Metric for Deep Reinforcement Learning. Jianda Chen, Sinno Jialin Pan |
| 2022 | Learning Robust Dynamics through Variational Sparse Gating. Arnav Kumar Jain, Shivakanth Sujit, Shruti Joshi, Vincent Michalski, Danijar Hafner, Samira Ebrahimi Kahou |
| 2022 | Learning Robust Rule Representations for Abstract Reasoning via Internal Inferences. Wenbo Zhang, Likai Tang, Site Mo, Xianggen Liu, Sen Song |
| 2022 | Learning State-Aware Visual Representations from Audible Interactions. Himangi Mittal, Pedro Morgado, Unnat Jain, Abhinav Gupta |
| 2022 | Learning Structure from the Ground up - Hierarchical Representation Learning by Chunking. Shuchen Wu, Noémi Élteto, Ishita Dasgupta, Eric Schulz |
| 2022 | Learning Substructure Invariance for Out-of-Distribution Molecular Representations. Nianzu Yang, Kaipeng Zeng, Qitian Wu, Xiaosong Jia, Junchi Yan |
| 2022 | Learning Superpoint Graph Cut for 3D Instance Segmentation. Le Hui, Linghua Tang, Yaqi Shen, Jin Xie, Jian Yang |
| 2022 | Learning Symmetric Rules with SATNet. Sangho Lim, Eun-Gyeol Oh, Hongseok Yang |
| 2022 | Learning Tractable Probabilistic Models from Inconsistent Local Estimates. Shasha Jin, Vasundhara Komaragiri, Tahrima Rahman, Vibhav Gogate |
| 2022 | Learning Two-Player Markov Games: Neural Function Approximation and Correlated Equilibrium. Chris Junchi Li, Dongruo Zhou, Quanquan Gu, Michael I. Jordan |
| 2022 | Learning Viewpoint-Agnostic Visual Representations by Recovering Tokens in 3D Space. Jinghuan Shang, Srijan Das, Michael S. Ryoo |
| 2022 | Learning a Condensed Frame for Memory-Efficient Video Class-Incremental Learning. Yixuan Pei, Zhiwu Qing, Jun Cen, Xiang Wang, Shiwei Zhang, Yaxiong Wang, Mingqian Tang, Nong Sang, Xueming Qian |
| 2022 | Learning and Covering Sums of Independent Random Variables with Unbounded Support. Alkis Kalavasis, Konstantinos Stavropoulos, Emmanouil Zampetakis |
| 2022 | Learning dynamics of deep linear networks with multiple pathways. Jianghong Shi, Eric Shea-Brown, Michael A. Buice |
| 2022 | Learning from Distributed Users in Contextual Linear Bandits Without Sharing the Context. Osama A. Hanna, Lin Yang, Christina Fragouli |
| 2022 | Learning from Few Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales. Tao Liu, P. R. Kumar, Ruida Zhou, Xi Liu |
| 2022 | Learning from Future: A Novel Self-Training Framework for Semantic Segmentation. Ye Du, Yujun Shen, Haochen Wang, Jingjing Fei, Wei Li, Liwei Wu, Rui Zhao, Zehua Fu, Qingjie Liu |
| 2022 | Learning from Label Proportions by Learning with Label Noise. Jianxin Zhang, Yutong Wang, Clayton Scott |
| 2022 | Learning from Stochastically Revealed Preference. John R. Birge, Xiaocheng Li, Chunlin Sun |
| 2022 | Learning from a Sample in Online Algorithms. C. J. Argue, Alan M. Frieze, Anupam Gupta, Christopher Seiler |
| 2022 | Learning in Congestion Games with Bandit Feedback. Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon S. Du |
| 2022 | Learning in Observable POMDPs, without Computationally Intractable Oracles. Noah Golowich, Ankur Moitra, Dhruv Rohatgi |
| 2022 | Learning interacting dynamical systems with latent Gaussian process ODEs. Çagatay Yildiz, Melih Kandemir, Barbara Rakitsch |
| 2022 | Learning low-dimensional generalizable natural features from retina using a U-net. Siwei Wang, Benjamin Hoshal, Elizabeth de Laittre, Thierry Mora, Michael Berry, Stephanie E. Palmer |
| 2022 | Learning on Arbitrary Graph Topologies via Predictive Coding. Tommaso Salvatori, Luca Pinchetti, Beren Millidge, Yuhang Song, Tianyi Bao, Rafal Bogacz, Thomas Lukasiewicz |
| 2022 | Learning on the Edge: Online Learning with Stochastic Feedback Graphs. Emmanuel Esposito, Federico Fusco, Dirk van der Hoeven, Nicolò Cesa-Bianchi |
| 2022 | Learning single-index models with shallow neural networks. Alberto Bietti, Joan Bruna, Clayton Sanford, Min Jae Song |
| 2022 | Learning sparse features can lead to overfitting in neural networks. Leonardo Petrini, Francesco Cagnetta, Eric Vanden-Eijnden, Matthieu Wyart |
| 2022 | Learning the Structure of Large Networked Systems Obeying Conservation Laws. Anirudh Rayas, Rajasekhar Anguluri, Gautam Dasarathy |
| 2022 | Learning to Accelerate Partial Differential Equations via Latent Global Evolution. Tailin Wu, Takashi Maruyama, Jure Leskovec |
| 2022 | Learning to Attack Federated Learning: A Model-based Reinforcement Learning Attack Framework. Henger Li, Xiaolin Sun, Zizhan Zheng |
| 2022 | Learning to Branch with Tree MDPs. Lara Scavuzzo, Feng Yang Chen, Didier Chételat, Maxime Gasse, Andrea Lodi, Neil Yorke-Smith, Karen I. Aardal |
| 2022 | Learning to Break the Loop: Analyzing and Mitigating Repetitions for Neural Text Generation. Jin Xu, Xiaojiang Liu, Jianhao Yan, Deng Cai, Huayang Li, Jian Li |
| 2022 | Learning to Compare Nodes in Branch and Bound with Graph Neural Networks. Abdel Ghani Labassi, Didier Chételat, Andrea Lodi |
| 2022 | Learning to Configure Computer Networks with Neural Algorithmic Reasoning. Luca Beurer-Kellner, Martin T. Vechev, Laurent Vanbever, Petar Velickovic |
| 2022 | Learning to Constrain Policy Optimization with Virtual Trust Region. Hung Le, Thommen Karimpanal George, Majid Abdolshah, Dung Nguyen, Kien Do, Sunil Gupta, Svetha Venkatesh |
| 2022 | Learning to Discover and Detect Objects. Vladimir Fomenko, Ismail Elezi, Deva Ramanan, Laura Leal-Taixé, Aljosa Osep |
| 2022 | Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs. Djordje Miladinovic, Kumar Shridhar, Kushal Jain, Max B. Paulus, Joachim M. Buhmann, Carl Allen |
| 2022 | Learning to Find Proofs and Theorems by Learning to Refine Search Strategies: The Case of Loop Invariant Synthesis. Jonathan Laurent, André Platzer |
| 2022 | Learning to Follow Instructions in Text-Based Games. Mathieu Tuli, Andrew C. Li, Pashootan Vaezipoor, Toryn Q. Klassen, Scott Sanner, Sheila A. McIlraith |
| 2022 | Learning to Generate Inversion-Resistant Model Explanations. Hoyong Jeong, Suyoung Lee, Sung Ju Hwang, Sooel Son |
| 2022 | Learning to Mitigate AI Collusion on Economic Platforms. Gianluca Brero, Eric Mibuari, Nicolas Lepore, David C. Parkes |
| 2022 | Learning to Navigate Wikipedia by Taking Random Walks. Manzil Zaheer, Kenneth Marino, Will Grathwohl, John Schultz, Wendy Shang, Sheila Babayan, Arun Ahuja, Ishita Dasgupta, Christine Kaeser-Chen, Rob Fergus |
| 2022 | Learning to Re-weight Examples with Optimal Transport for Imbalanced Classification. Dandan Guo, Zhuo Li, Meixi Zheng, He Zhao, Mingyuan Zhou, Hongyuan Zha |
| 2022 | Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures. Emmanuel Abbe, Samy Bengio, Elisabetta Cornacchia, Jon M. Kleinberg, Aryo Lotfi, Maithra Raghu, Chiyuan Zhang |
| 2022 | Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations. Ivan Marisca, Andrea Cini, Cesare Alippi |
| 2022 | Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graphs. Ruijie Wang, Zheng Li, Dachun Sun, Shengzhong Liu, Jinning Li, Bing Yin, Tarek F. Abdelzaher |
| 2022 | Learning to Scaffold: Optimizing Model Explanations for Teaching. Patrick Fernandes, Marcos V. Treviso, Danish Pruthi, André F. T. Martins, Graham Neubig |
| 2022 | Learning to Share in Networked Multi-Agent Reinforcement Learning. Yuxuan Yi, Ge Li, Yaowei Wang, Zongqing Lu |
| 2022 | Learning with convolution and pooling operations in kernel methods. Theodor Misiakiewicz, Song Mei |
| 2022 | Learning with little mixing. Ingvar M. Ziemann, Stephen Tu |
| 2022 | Learning-Augmented Algorithms for Online Linear and Semidefinite Programming. Elena Grigorescu, Young-San Lin, Sandeep Silwal, Maoyuan Song, Samson Zhou |
| 2022 | Learning-based Motion Planning in Dynamic Environments Using GNNs and Temporal Encoding. Ruipeng Zhang, Chenning Yu, Jingkai Chen, Chuchu Fan, Sicun Gao |
| 2022 | Left Heavy Tails and the Effectiveness of the Policy and Value Networks in DNN-based best-first search for Sokoban Planning. Dieqiao Feng, Carla P. Gomes, Bart Selman |
| 2022 | Less-forgetting Multi-lingual Fine-tuning. Yuren Mao, Yaobo Liang, Nan Duan, Haobo Wang, Kai Wang, Lu Chen, Yunjun Gao |
| 2022 | Let Images Give You More: Point Cloud Cross-Modal Training for Shape Analysis. Xu Yan, Heshen Zhan, Chaoda Zheng, Jiantao Gao, Ruimao Zhang, Shuguang Cui, Zhen Li |
| 2022 | Lethal Dose Conjecture on Data Poisoning. Wenxiao Wang, Alexander Levine, Soheil Feizi |
| 2022 | Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare. Shengpu Tang, Maggie Makar, Michael W. Sjoding, Finale Doshi-Velez, Jenna Wiens |
| 2022 | Leveraging Inter-Layer Dependency for Post -Training Quantization. Changbao Wang, Dandan Zheng, Yuanliu Liu, Liang Li |
| 2022 | Leveraging the Hints: Adaptive Bidding in Repeated First-Price Auctions. Wei Zhang, Yanjun Han, Zhengyuan Zhou, Aaron Flores, Tsachy Weissman |
| 2022 | LieGG: Studying Learned Lie Group Generators. Artem Moskalev, Anna Sepliarskaia, Ivan Sosnovik, Arnold W. M. Smeulders |
| 2022 | Lifelong Neural Predictive Coding: Learning Cumulatively Online without Forgetting. Alexander Ororbia, Ankur Mali, C. Lee Giles, Daniel Kifer |
| 2022 | Lifting Weak Supervision To Structured Prediction. Harit Vishwakarma, Frederic Sala |
| 2022 | Lifting the Information Ratio: An Information-Theoretic Analysis of Thompson Sampling for Contextual Bandits. Gergely Neu, Julia Olkhovskaya, Matteo Papini, Ludovic Schwartz |
| 2022 | Linear Label Ranking with Bounded Noise. Dimitris Fotakis, Alkis Kalavasis, Vasilis Kontonis, Christos Tzamos |
| 2022 | Linear tree shap. Peng Yu, Albert Bifet, Jesse Read, Chao Xu |
| 2022 | Lipschitz Bandits with Batched Feedback. Yasong Feng, Zengfeng Huang, Tianyu Wang |
| 2022 | List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering. Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas |
| 2022 | List-Decodable Sparse Mean Estimation. Shiwei Zeng, Jie Shen |
| 2022 | Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF. Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi, Florence d'Alché-Buc, Gaël Richard |
| 2022 | LiteTransformerSearch: Training-free Neural Architecture Search for Efficient Language Models. Mojan Javaheripi, Gustavo de Rosa, Subhabrata Mukherjee, Shital Shah, Tomasz Religa, Caio César Teodoro Mendes, Sébastien Bubeck, Farinaz Koushanfar, Debadeepta Dey |
| 2022 | LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation. Geon-Hyeong Kim, Jongmin Lee, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim |
| 2022 | Local Bayesian optimization via maximizing probability of descent. Quan Nguyen, Kaiwen Wu, Jacob R. Gardner, Roman Garnett |
| 2022 | Local Identifiability of Deep ReLU Neural Networks: the Theory. Joachim Bona-Pellissier, François Malgouyres, François Bachoc |
| 2022 | Local Latent Space Bayesian Optimization over Structured Inputs. Natalie Maus, Haydn Thomas Jones, Juston Moore, Matt J. Kusner, John Bradshaw, Jacob R. Gardner |
| 2022 | Local Linear Convergence of Gradient Methods for Subspace Optimization via Strict Complementarity. Ron Fisher, Dan Garber |
| 2022 | Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions. Haanvid Lee, Jongmin Lee, Yunseon Choi, Wonseok Jeon, Byung-Jun Lee, Yung-Kyun Noh, Kee-Eung Kim |
| 2022 | Local Spatiotemporal Representation Learning for Longitudinally-consistent Neuroimage Analysis. Mengwei Ren, Neel Dey, Martin Styner, Kelly N. Botteron, Guido Gerig |
| 2022 | Local-Global MCMC kernels: the best of both worlds. Sergey Samsonov, Evgeny Lagutin, Marylou Gabrié, Alain Durmus, Alexey Naumov, Eric Moulines |
| 2022 | Locally Hierarchical Auto-Regressive Modeling for Image Generation. Tackgeun You, Saehoon Kim, Chiheon Kim, Doyup Lee, Bohyung Han |
| 2022 | Locating and Editing Factual Associations in GPT. Kevin Meng, David Bau, Alex Andonian, Yonatan Belinkov |
| 2022 | Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy. Jordan Awan, Jinshuo Dong |
| 2022 | Log-Linear-Time Gaussian Processes Using Binary Tree Kernels. Michael K. Cohen, Samuel Daulton, Michael A. Osborne |
| 2022 | Log-Polar Space Convolution Layers. Bing Su, Ji-Rong Wen |
| 2022 | LogiGAN: Learning Logical Reasoning via Adversarial Pre-training. Xinyu Pi, Wanjun Zhong, Yan Gao, Nan Duan, Jian-Guang Lou |
| 2022 | Logical Activation Functions: Logit-space equivalents of Probabilistic Boolean Operators. Scott C. Lowe, Robert Earle, Jason d'Eon, Thomas Trappenberg, Sageev Oore |
| 2022 | Logical Credal Networks. Radu Marinescu, Haifeng Qian, Alexander G. Gray, Debarun Bhattacharjya, Francisco Barahona, Tian Gao, Ryan Riegel, Pravinda Sahu |
| 2022 | Long Range Graph Benchmark. Vijay Prakash Dwivedi, Ladislav Rampásek, Michael Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini |
| 2022 | Long-Form Video-Language Pre-Training with Multimodal Temporal Contrastive Learning. Yuchong Sun, Hongwei Xue, Ruihua Song, Bei Liu, Huan Yang, Jianlong Fu |
| 2022 | Look Around and Refer: 2D Synthetic Semantics Knowledge Distillation for 3D Visual Grounding. Eslam Mohamed Bakr, Yasmeen Alsaedy, Mohamed Elhoseiny |
| 2022 | Look More but Care Less in Video Recognition. Yitian Zhang, Yue Bai, Huan Wang, Yi Xu, Yun Fu |
| 2022 | Look where you look! Saliency-guided Q-networks for generalization in visual Reinforcement Learning. David Bertoin, Adil Zouitine, Mehdi Zouitine, Emmanuel Rachelson |
| 2022 | Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing. Yonggan Fu, Yang Zhang, Kaizhi Qian, Zhifan Ye, Zhongzhi Yu, Cheng-I Jeff Lai, Yingyan (Celine) Lin |
| 2022 | Lost in Latent Space: Examining failures of disentangled models at combinatorial generalisation. Milton Llera Montero, Jeffrey S. Bowers, Rui Ponte Costa, Casimir J. H. Ludwig, Gaurav Malhotra |
| 2022 | Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks. Mansheej Paul, Brett W. Larsen, Surya Ganguli, Jonathan Frankle, Gintare Karolina Dziugaite |
| 2022 | Low-Rank Modular Reinforcement Learning via Muscle Synergy. Heng Dong, Tonghan Wang, Jiayuan Liu, Chongjie Zhang |
| 2022 | Low-rank Optimal Transport: Approximation, Statistics and Debiasing. Meyer Scetbon, Marco Cuturi |
| 2022 | Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations. Steffen Schotthöfer, Emanuele Zangrando, Jonas Kusch, Gianluca Ceruti, Francesco Tudisco |
| 2022 | Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression. Xinmeng Huang, Yiming Chen, Wotao Yin, Kun Yuan |
| 2022 | Lower Bounds on Randomly Preconditioned Lasso via Robust Sparse Designs. Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi |
| 2022 | Luckiness in Multiscale Online Learning. Wouter M. Koolen, Muriel Felipe Pérez-Ortiz |
| 2022 | M$^4$I: Multi-modal Models Membership Inference. Pingyi Hu, Zihan Wang, Ruoxi Sun, Hu Wang, Minhui Xue |
| 2022 | M2N: Mesh Movement Networks for PDE Solvers. Wenbin Song, Mingrui Zhang, Joseph G. Wallwork, Junpeng Gao, Zheng Tian, Fanglei Sun, Matthew D. Piggott, Junqing Chen, Zuoqiang Shi, Xiang Chen, Jun Wang |
| 2022 | M4Singer: A Multi-Style, Multi-Singer and Musical Score Provided Mandarin Singing Corpus. Lichao Zhang, Ruiqi Li, Shoutong Wang, Liqun Deng, Jinglin Liu, Yi Ren, Jinzheng He, Rongjie Huang, Jieming Zhu, Xiao Chen, Zhou Zhao |
| 2022 | MABSplit: Faster Forest Training Using Multi-Armed Bandits. Mo Tiwari, Ryan Kang, Jaeyong Lee, Chris Piech, Ilan Shomorony, Sebastian Thrun, Martin J. Zhang |
| 2022 | MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields. Ilyes Batatia, Dávid Péter Kovács, Gregor N. C. Simm, Christoph Ortner, Gábor Csányi |
| 2022 | MACK: Multimodal Aligned Conceptual Knowledge for Unpaired Image-text Matching. Yan Huang, Yuming Wang, Yunan Zeng, Liang Wang |
| 2022 | MATE: Benchmarking Multi-Agent Reinforcement Learning in Distributed Target Coverage Control. Xuehai Pan, Mickel Liu, Fangwei Zhong, Yaodong Yang, Song-Chun Zhu, Yizhou Wang |
| 2022 | MAgNet: Mesh Agnostic Neural PDE Solver. Oussama Boussif, Yoshua Bengio, Loubna Benabbou, Dan Assouline |
| 2022 | MAtt: A Manifold Attention Network for EEG Decoding. Yue-Ting Pan, Jing-Lun Chou, Chun-Shu Wei |
| 2022 | MBW: Multi-view Bootstrapping in the Wild. Mosam Dabhi, Chaoyang Wang, Tim Clifford, László A. Jeni, Ian R. Fasel, Simon Lucey |
| 2022 | MCL-GAN: Generative Adversarial Networks with Multiple Specialized Discriminators. Jinyoung Choi, Bohyung Han |
| 2022 | MCMAE: Masked Convolution Meets Masked Autoencoders. Peng Gao, Teli Ma, Hongsheng Li, Ziyi Lin, Jifeng Dai, Yu Qiao |
| 2022 | MCVD - Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation. Vikram Voleti, Alexia Jolicoeur-Martineau, Chris Pal |
| 2022 | MEMO: Test Time Robustness via Adaptation and Augmentation. Marvin Zhang, Sergey Levine, Chelsea Finn |
| 2022 | METS-CoV: A Dataset of Medical Entity and Targeted Sentiment on COVID-19 Related Tweets. Peilin Zhou, Zeqiang Wang, Dading Chong, Zhijiang Guo, Yining Hua, Zichang Su, Zhiyang Teng, Jiageng Wu, Jie Yang |
| 2022 | MExMI: Pool-based Active Model Extraction Crossover Membership Inference. Yaxin Xiao, Qingqing Ye, Haibo Hu, Huadi Zheng, Chengfang Fang, Jie Shi |
| 2022 | MGNNI: Multiscale Graph Neural Networks with Implicit Layers. Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao |
| 2022 | MOMA-LRG: Language-Refined Graphs for Multi-Object Multi-Actor Activity Parsing. Zelun Luo, Zane Durante, Linden Li, Wanze Xie, Ruochen Liu, Emily Jin, Zhuoyi Huang, Lun Yu Li, Jiajun Wu, Juan Carlos Niebles, Ehsan Adeli, Fei-Fei Li |
| 2022 | MORA: Improving Ensemble Robustness Evaluation with Model Reweighing Attack. Yunrui Yu, Xitong Gao, Cheng-Zhong Xu |
| 2022 | MOVE: Unsupervised Movable Object Segmentation and Detection. Adam Bielski, Paolo Favaro |
| 2022 | MSDS: A Large-Scale Chinese Signature and Token Digit String Dataset for Handwriting Verification. Peirong Zhang, Jiajia Jiang, Yuliang Liu, Lianwen Jin |
| 2022 | MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction. Jorge Quesada, Lakshmi Sathidevi, Ran Liu, Nauman Ahad, Joy M. Jackson, Mehdi Azabou, Jingyun Xiao, Christopher Liding, Matthew Jin, Carolina Urzay, William R. Gray Roncal, Erik C. Johnson, Eva L. Dyer |
| 2022 | MVP-N: A Dataset and Benchmark for Real-World Multi-View Object Classification. Ren Wang, Jiayue Wang, Tae Sung Kim, Jinsung Kim, Hyuk-Jae Lee |
| 2022 | Make Sharpness-Aware Minimization Stronger: A Sparsified Perturbation Approach. Peng Mi, Li Shen, Tianhe Ren, Yiyi Zhou, Xiaoshuai Sun, Rongrong Ji, Dacheng Tao |
| 2022 | Make Some Noise: Reliable and Efficient Single-Step Adversarial Training. Pau de Jorge Aranda, Adel Bibi, Riccardo Volpi, Amartya Sanyal, Philip H. S. Torr, Grégory Rogez, Puneet K. Dokania |
| 2022 | Make an Omelette with Breaking Eggs: Zero-Shot Learning for Novel Attribute Synthesis. Yu Hsuan Li, Tzu-Yin Chao, Ching-Chun Huang, Pin-Yu Chen, Wei-Chen Chiu |
| 2022 | Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels. Mohamad Amin Mohamadi, Wonho Bae, Danica J. Sutherland |
| 2022 | Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure. Paul Novello, Thomas Fel, David Vigouroux |
| 2022 | Manifold Interpolating Optimal-Transport Flows for Trajectory Inference. Guillaume Huguet, Daniel Sumner Magruder, Alexander Tong, Oluwadamilola Fasina, Manik Kuchroo, Guy Wolf, Smita Krishnaswamy |
| 2022 | Margin-Based Few-Shot Class-Incremental Learning with Class-Level Overfitting Mitigation. Yixiong Zou, Shanghang Zhang, Yuhua Li, Ruixuan Li |
| 2022 | Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients. Kyurae Kim, Jisu Oh, Jacob R. Gardner, Adji Bousso Dieng, Hongseok Kim |
| 2022 | Markovian Interference in Experiments. Vivek F. Farias, Andrew A. Li, Tianyi Peng, Andrew Zheng |
| 2022 | Marksman Backdoor: Backdoor Attacks with Arbitrary Target Class. Khoa D. Doan, Yingjie Lao, Ping Li |
| 2022 | Mask Matching Transformer for Few-Shot Segmentation. Siyu Jiao, Gengwei Zhang, Shant Navasardyan, Ling Chen, Yao Zhao, Yunchao Wei, Honghui Shi |
| 2022 | Mask-based Latent Reconstruction for Reinforcement Learning. Tao Yu, Zhizheng Zhang, Cuiling Lan, Yan Lu, Zhibo Chen |
| 2022 | MaskPlace: Fast Chip Placement via Reinforced Visual Representation Learning. Yao Lai, Yao Mu, Ping Luo |
| 2022 | MaskTune: Mitigating Spurious Correlations by Forcing to Explore. Saeid Asgari Taghanaki, Aliasghar Khani, Fereshte Khani, Ali Gholami, Linh Tran, Ali Mahdavi-Amiri, Ghassan Hamarneh |
| 2022 | Masked Autoencoders As Spatiotemporal Learners. Christoph Feichtenhofer, Haoqi Fan, Yanghao Li, Kaiming He |
| 2022 | Masked Autoencoders that Listen. Po-Yao Huang, Hu Xu, Juncheng Li, Alexei Baevski, Michael Auli, Wojciech Galuba, Florian Metze, Christoph Feichtenhofer |
| 2022 | Masked Autoencoding for Scalable and Generalizable Decision Making. Fangchen Liu, Hao Liu, Aditya Grover, Pieter Abbeel |
| 2022 | Masked Generative Adversarial Networks are Data-Efficient Generation Learners. Jiaxing Huang, Kaiwen Cui, Dayan Guan, Aoran Xiao, Fangneng Zhan, Shijian Lu, Shengcai Liao, Eric P. Xing |
| 2022 | Masked Prediction: A Parameter Identifiability View. Bingbin Liu, Daniel J. Hsu, Pradeep Ravikumar, Andrej Risteski |
| 2022 | Matching in Multi-arm Bandit with Collision. Yirui Zhang, Siwei Wang, Zhixuan Fang |
| 2022 | Matrix Multiplicative Weights Updates in Quantum Zero-Sum Games: Conservation Laws & Recurrence. Rahul Jain, Georgios Piliouras, Ryann Sim |
| 2022 | Matryoshka Representation Learning. Aditya Kusupati, Gantavya Bhatt, Aniket Rege, Matthew Wallingford, Aditya Sinha, Vivek Ramanujan, William Howard-Snyder, Kaifeng Chen, Sham M. Kakade, Prateek Jain, Ali Farhadi |
| 2022 | Max-Min Off-Policy Actor-Critic Method Focusing on Worst-Case Robustness to Model Misspecification. Takumi Tanabe, Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto |
| 2022 | Maximizing Revenue under Market Shrinkage and Market Uncertainty. Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm |
| 2022 | Maximizing and Satisficing in Multi-armed Bandits with Graph Information. Parth Thaker, Mohit Malu, Nikhil Rao, Gautam Dasarathy |
| 2022 | Maximum Class Separation as Inductive Bias in One Matrix. Tejaswi Kasarla, Gertjan J. Burghouts, Max van Spengler, Elise van der Pol, Rita Cucchiara, Pascal Mettes |
| 2022 | Maximum Common Subgraph Guided Graph Retrieval: Late and Early Interaction Networks. Indradyumna Roy, Soumen Chakrabarti, Abir De |
| 2022 | Maximum Likelihood Training of Implicit Nonlinear Diffusion Model. Dongjun Kim, Byeonghu Na, Se Jung Kwon, Dongsoo Lee, Wanmo Kang, Il-Chul Moon |
| 2022 | Maximum a posteriori natural scene reconstruction from retinal ganglion cells with deep denoiser priors. Eric Wu, Nora Brackbill, Alexander Sher, Alan M. Litke, Eero P. Simoncelli, E. J. Chichilnisky |
| 2022 | Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees. Siliang Zeng, Chenliang Li, Alfredo García, Mingyi Hong |
| 2022 | Mean Estimation in High-Dimensional Binary Markov Gaussian Mixture Models. Yihan Zhang, Nir Weinberger |
| 2022 | Mean Estimation with User-level Privacy under Data Heterogeneity. Rachel Cummings, Vitaly Feldman, Audra McMillan, Kunal Talwar |
| 2022 | Measures of Information Reflect Memorization Patterns. Rachit Bansal, Danish Pruthi, Yonatan Belinkov |
| 2022 | Measuring Data Reconstruction Defenses in Collaborative Inference Systems. Mengda Yang, Ziang Li, Juan Wang, Hongxin Hu, Ao Ren, Xiaoyang Xu, Wenzhe Yi |
| 2022 | Measuring and Reducing Model Update Regression in Structured Prediction for NLP. Deng Cai, Elman Mansimov, Yi-An Lai, Yixuan Su, Lei Shu, Yi Zhang |
| 2022 | Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models. Kushal Tirumala, Aram H. Markosyan, Luke Zettlemoyer, Armen Aghajanyan |
| 2022 | Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization. Simone Bombari, Mohammad Hossein Amani, Marco Mondelli |
| 2022 | Memory Efficient Continual Learning with Transformers. Beyza Ermis, Giovanni Zappella, Martin Wistuba, Aditya Rawal, Cédric Archambeau |
| 2022 | Memory safe computations with XLA compiler. Artem Artemev, Yuze An, Tilman Roeder, Mark van der Wilk |
| 2022 | Merging Models with Fisher-Weighted Averaging. Michael Matena, Colin Raffel |
| 2022 | Mesoscopic modeling of hidden spiking neurons. Shuqi Wang, Valentin Schmutz, Guillaume Bellec, Wulfram Gerstner |
| 2022 | Meta Reinforcement Learning with Finite Training Tasks - a Density Estimation Approach. Zohar Rimon, Aviv Tamar, Gilad Adler |
| 2022 | Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification. Ihsan Ullah, Dustin Carrión-Ojeda, Sergio Escalera, Isabelle Guyon, Mike Huisman, Felix Mohr, Jan N. van Rijn, Haozhe Sun, Joaquin Vanschoren, Phan Anh Vu |
| 2022 | Meta-Auto-Decoder for Solving Parametric Partial Differential Equations. Xiang Huang, Zhanhong Ye, Hongsheng Liu, Beiji Shi, Zidong Wang, Kang Yang, Yang Li, Min Wang, Haotian Chu, Fan Yu, Bei Hua, Lei Chen, Bin Dong |
| 2022 | Meta-Complementing the Semantics of Short Texts in Neural Topic Models. Delvin Ce Zhang, Hady W. Lauw |
| 2022 | Meta-DMoE: Adapting to Domain Shift by Meta-Distillation from Mixture-of-Experts. Tao Zhong, Zhixiang Chi, Li Gu, Yang Wang, Yuanhao Yu, Jin Tang |
| 2022 | Meta-Learning Dynamics Forecasting Using Task Inference. Rui Wang, Robin Walters, Rose Yu |
| 2022 | Meta-Learning with Self-Improving Momentum Target. Jihoon Tack, Jongjin Park, Hankook Lee, Jaeho Lee, Jinwoo Shin |
| 2022 | Meta-Query-Net: Resolving Purity-Informativeness Dilemma in Open-set Active Learning. Dongmin Park, Yooju Shin, Jihwan Bang, Youngjun Lee, Hwanjun Song, Jae-Gil Lee |
| 2022 | Meta-Reinforcement Learning with Self-Modifying Networks. Mathieu Chalvidal, Thomas Serre, Rufin VanRullen |
| 2022 | Meta-Reward-Net: Implicitly Differentiable Reward Learning for Preference-based Reinforcement Learning. Runze Liu, Fengshuo Bai, Yali Du, Yaodong Yang |
| 2022 | Meta-ticket: Finding optimal subnetworks for few-shot learning within randomly initialized neural networks. Daiki Chijiwa, Shin'ya Yamaguchi, Atsutoshi Kumagai, Yasutoshi Ida |
| 2022 | MetaMask: Revisiting Dimensional Confounder for Self-Supervised Learning. Jiangmeng Li, Wenwen Qiang, Yanan Zhang, Wenyi Mo, Changwen Zheng, Bing Su, Hui Xiong |
| 2022 | MetaTeacher: Coordinating Multi-Model Domain Adaptation for Medical Image Classification. Zhenbin Wang, Mao Ye, Xiatian Zhu, Liuhan Peng, Liang Tian, Yingying Zhu |
| 2022 | MetricFormer: A Unified Perspective of Correlation Exploring in Similarity Learning. Jiexi Yan, Erkun Yang, Cheng Deng, Heng Huang |
| 2022 | Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders. Kiarash Zahirnia, Oliver Schulte, Parmis Naddaf, Ke Li |
| 2022 | Mildly Conservative Q-Learning for Offline Reinforcement Learning. Jiafei Lyu, Xiaoteng Ma, Xiu Li, Zongqing Lu |
| 2022 | MinVIS: A Minimal Video Instance Segmentation Framework without Video-based Training. De-An Huang, Zhiding Yu, Anima Anandkumar |
| 2022 | Mind Reader: Reconstructing complex images from brain activities. Sikun Lin, Thomas Sprague, Ambuj K. Singh |
| 2022 | Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning. Weixin Liang, Yuhui Zhang, Yongchan Kwon, Serena Yeung, James Y. Zou |
| 2022 | MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge. Linxi Fan, Guanzhi Wang, Yunfan Jiang, Ajay Mandlekar, Yuncong Yang, Haoyi Zhu, Andrew Tang, De-An Huang, Yuke Zhu, Anima Anandkumar |
| 2022 | Mingling Foresight with Imagination: Model-Based Cooperative Multi-Agent Reinforcement Learning. Zhiwei Xu, Dapeng Li, Bin Zhang, Yuan Zhan, Yunpeng Bai, Guoliang Fan |
| 2022 | Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification. Junpei Komiyama, Taira Tsuchiya, Junya Honda |
| 2022 | Minimax Optimal Fixed-Budget Best Arm Identification in Linear Bandits. Junwen Yang, Vincent Y. F. Tan |
| 2022 | Minimax Optimal Online Imitation Learning via Replay Estimation. Gokul Swamy, Nived Rajaraman, Matthew Peng, Sanjiban Choudhury, J. Andrew Bagnell, Steven Wu, Jiantao Jiao, Kannan Ramchandran |
| 2022 | Minimax Regret for Cascading Bandits. Daniel Vial, Sujay Sanghavi, Sanjay Shakkottai, R. Srikant |
| 2022 | Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model. Gen Li, Yuejie Chi, Yuting Wei, Yuxin Chen |
| 2022 | Mining Multi-Label Samples from Single Positive Labels. Youngin Cho, DaeJin Kim, Mohammad Azam Khan, Jaegul Choo |
| 2022 | Mining Unseen Classes via Regional Objectness: A Simple Baseline for Incremental Segmentation. Zekang Zhang, Guangyu Gao, Zhiyuan Fang, Jianbo Jiao, Yunchao Wei |
| 2022 | Mirror Descent Maximizes Generalized Margin and Can Be Implemented Efficiently. Haoyuan Sun, Kwangjun Ahn, Christos Thrampoulidis, Navid Azizan |
| 2022 | Mirror Descent with Relative Smoothness in Measure Spaces, with application to Sinkhorn and EM. Pierre-Cyril Aubin-Frankowski, Anna Korba, Flavien Léger |
| 2022 | Mismatched No More: Joint Model-Policy Optimization for Model-Based RL. Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov |
| 2022 | MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models. Erdun Gao, Ignavier Ng, Mingming Gong, Li Shen, Wei Huang, Tongliang Liu, Kun Zhang, Howard D. Bondell |
| 2022 | Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo. Ignacio Peis, Chao Ma, José Miguel Hernández-Lobato |
| 2022 | Misspecified Phase Retrieval with Generative Priors. Zhaoqiang Liu, Xinshao Wang, Jiulong Liu |
| 2022 | Mix and Reason: Reasoning over Semantic Topology with Data Mixing for Domain Generalization. Chaoqi Chen, Luyao Tang, Feng Liu, Gangming Zhao, Yue Huang, Yizhou Yu |
| 2022 | Mixture-of-Experts with Expert Choice Routing. Yanqi Zhou, Tao Lei, Hanxiao Liu, Nan Du, Yanping Huang, Vincent Y. Zhao, Andrew M. Dai, Zhifeng Chen, Quoc V. Le, James Laudon |
| 2022 | MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control. Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew J. Hausknecht |
| 2022 | MoCoDA: Model-based Counterfactual Data Augmentation. Silviu Pitis, Elliot Creager, Ajay Mandlekar, Animesh Garg |
| 2022 | MoGDE: Boosting Mobile Monocular 3D Object Detection with Ground Depth Estimation. Yunsong Zhou, Quan Liu, Hongzi Zhu, Yunzhe Li, Shan Chang, Minyi Guo |
| 2022 | MoVQ: Modulating Quantized Vectors for High-Fidelity Image Generation. Chuanxia Zheng, Tung-Long Vuong, Jianfei Cai, Dinh Phung |
| 2022 | Model Preserving Compression for Neural Networks. Jerry Chee, Megan Flynn, Anil Damle, Christopher De Sa |
| 2022 | Model Zoos: A Dataset of Diverse Populations of Neural Network Models. Konstantin Schürholt, Diyar Taskiran, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth |
| 2022 | Model-Based Imitation Learning for Urban Driving. Anthony Hu, Gianluca Corrado, Nicolas Griffiths, Zachary Murez, Corina Gurau, Hudson Yeo, Alex Kendall, Roberto Cipolla, Jamie Shotton |
| 2022 | Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief. Kaiyang Guo, Yunfeng Shao, Yanhui Geng |
| 2022 | Model-Based Opponent Modeling. Xiaopeng Yu, Jiechuan Jiang, Wanpeng Zhang, Haobin Jiang, Zongqing Lu |
| 2022 | Model-based Lifelong Reinforcement Learning with Bayesian Exploration. Haotian Fu, Shangqun Yu, Michael Littman, George Konidaris |
| 2022 | Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity. Alekh Agarwal, Tong Zhang |
| 2022 | Model-based Safe Deep Reinforcement Learning via a Constrained Proximal Policy Optimization Algorithm. Ashish Kumar Jayant, Shalabh Bhatnagar |
| 2022 | Modeling Human Exploration Through Resource-Rational Reinforcement Learning. Marcel Binz, Eric Schulz |
| 2022 | Modeling Transitivity and Cyclicity in Directed Graphs via Binary Code Box Embeddings. Dongxu Zhang, Michael Boratko, Cameron Musco, Andrew McCallum |
| 2022 | Modeling the Machine Learning Multiverse. Samuel J. Bell, Onno Kampman, Jesse Dodge, Neil D. Lawrence |
| 2022 | Models Out of Line: A Fourier Lens on Distribution Shift Robustness. Sara Fridovich-Keil, Brian R. Bartoldson, James Diffenderfer, Bhavya Kailkhura, Timo Bremer |
| 2022 | Moderate-fitting as a Natural Backdoor Defender for Pre-trained Language Models. Biru Zhu, Yujia Qin, Ganqu Cui, Yangyi Chen, Weilin Zhao, Chong Fu, Yangdong Deng, Zhiyuan Liu, Jingang Wang, Wei Wu, Maosong Sun, Ming Gu |
| 2022 | Modular Flows: Differential Molecular Generation. Yogesh Verma, Samuel Kaski, Markus Heinonen, Vikas Garg |
| 2022 | Module-Aware Optimization for Auxiliary Learning. Hong Chen, Xin Wang, Yue Liu, Yuwei Zhou, Chaoyu Guan, Wenwu Zhu |
| 2022 | Molecule Generation by Principal Subgraph Mining and Assembling. Xiangzhe Kong, Wenbing Huang, Zhixing Tan, Yang Liu |
| 2022 | Moment Distributionally Robust Tree Structured Prediction. Yeshu Li, Danyal Saeed, Xinhua Zhang, Brian D. Ziebart, Kevin Gimpel |
| 2022 | Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation. Kien Do, Hung Le, Dung Nguyen, Dang Nguyen, Haripriya Harikumar, Truyen Tran, Santu Rana, Svetha Venkatesh |
| 2022 | Momentum Aggregation for Private Non-convex ERM. Hoang Tran, Ashok Cutkosky |
| 2022 | MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstruction. Zehao Yu, Songyou Peng, Michael Niemeyer, Torsten Sattler, Andreas Geiger |
| 2022 | Monocular Dynamic View Synthesis: A Reality Check. Hang Gao, Ruilong Li, Shubham Tulsiani, Bryan Russell, Angjoo Kanazawa |
| 2022 | Monte Carlo Augmented Actor-Critic for Sparse Reward Deep Reinforcement Learning from Suboptimal Demonstrations. Albert Wilcox, Ashwin Balakrishna, Jules Dedieu, Wyame Benslimane, Daniel S. Brown, Ken Goldberg |
| 2022 | Monte Carlo Tree Descent for Black-Box Optimization. Yaoguang Zhai, Sicun Gao |
| 2022 | Monte Carlo Tree Search based Variable Selection for High Dimensional Bayesian Optimization. Lei Song, Ke Xue, Xiaobin Huang, Chao Qian |
| 2022 | MorphTE: Injecting Morphology in Tensorized Embeddings. Guobing Gan, Peng Zhang, Sunzhu Li, Xiuqing Lu, Benyou Wang |
| 2022 | Most Activation Functions Can Win the Lottery Without Excessive Depth. Rebekka Burkholz |
| 2022 | Motion Transformer with Global Intention Localization and Local Movement Refinement. Shaoshuai Shi, Li Jiang, Dengxin Dai, Bernt Schiele |
| 2022 | Movement Penalized Bayesian Optimization with Application to Wind Energy Systems. Shyam Sundhar Ramesh, Pier Giuseppe Sessa, Andreas Krause, Ilija Bogunovic |
| 2022 | MsSVT: Mixed-scale Sparse Voxel Transformer for 3D Object Detection on Point Clouds. Shaocong Dong, Lihe Ding, Haiyang Wang, Tingfa Xu, Xinli Xu, Jie Wang, Ziyang Bian, Ying Wang, Jianan Li |
| 2022 | Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging. Edwige Cyffers, Mathieu Even, Aurélien Bellet, Laurent Massoulié |
| 2022 | Multi-Agent Reinforcement Learning is a Sequence Modeling Problem. Muning Wen, Jakub Grudzien Kuba, Runji Lin, Weinan Zhang, Ying Wen, Jun Wang, Yaodong Yang |
| 2022 | Multi-Class $H$-Consistency Bounds. Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong |
| 2022 | Multi-Fidelity Best-Arm Identification. Riccardo Poiani, Alberto Maria Metelli, Marcello Restelli |
| 2022 | Multi-Game Decision Transformers. Kuang-Huei Lee, Ofir Nachum, Mengjiao Yang, Lisa Lee, Daniel Freeman, Sergio Guadarrama, Ian Fischer, Winnie Xu, Eric Jang, Henryk Michalewski, Igor Mordatch |
| 2022 | Multi-Granularity Cross-modal Alignment for Generalized Medical Visual Representation Learning. Fuying Wang, Yuyin Zhou, Shujun Wang, Varut Vardhanabhuti, Lequan Yu |
| 2022 | Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization. Weijia Zhang, Xuanhui Zhang, Hanwen Deng, Min-Ling Zhang |
| 2022 | Multi-LexSum: Real-world Summaries of Civil Rights Lawsuits at Multiple Granularities. Zejiang Shen, Kyle Lo, Lauren Yu, Nathan Dahlberg, Margo Schlanger, Doug Downey |
| 2022 | Multi-Lingual Acquisition on Multimodal Pre-training for Cross-modal Retrieval. Liang Zhang, Anwen Hu, Qin Jin |
| 2022 | Multi-Objective Deep Learning with Adaptive Reference Vectors. Weiyu Chen, James T. Kwok |
| 2022 | Multi-Sample Training for Neural Image Compression. Tongda Xu, Yan Wang, Dailan He, Chenjian Gao, Han Gao, Kunzan Liu, Hongwei Qin |
| 2022 | Multi-Scale Adaptive Network for Single Image Denoising. Yuanbiao Gou, Peng Hu, Jiancheng Lv, Joey Tianyi Zhou, Xi Peng |
| 2022 | Multi-agent Dynamic Algorithm Configuration. Ke Xue, Jiacheng Xu, Lei Yuan, Miqing Li, Chao Qian, Zongzhang Zhang, Yang Yu |
| 2022 | Multi-agent Performative Prediction with Greedy Deployment and Consensus Seeking Agents. Qiang Li, Chung-Yiu Yau, Hoi-To Wai |
| 2022 | Multi-block Min-max Bilevel Optimization with Applications in Multi-task Deep AUC Maximization. Quanqi Hu, Yongjian Zhong, Tianbao Yang |
| 2022 | Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization. Wei Jiang, Gang Li, Yibo Wang, Lijun Zhang, Tianbao Yang |
| 2022 | Multi-dataset Training of Transformers for Robust Action Recognition. Junwei Liang, Enwei Zhang, Jun Zhang, Chunhua Shen |
| 2022 | Multi-fidelity Monte Carlo: a pseudo-marginal approach. Diana Cai, Ryan P. Adams |
| 2022 | Multi-layer State Evolution Under Random Convolutional Design. Max Daniels, Cédric Gerbelot, Florent Krzakala, Lenka Zdeborová |
| 2022 | Multi-modal Grouping Network for Weakly-Supervised Audio-Visual Video Parsing. Shentong Mo, Yapeng Tian |
| 2022 | Multi-objective Deep Data Generation with Correlated Property Control. Shiyu Wang, Xiaojie Guo, Xuanyang Lin, Bo Pan, Yuanqi Du, Yinkai Wang, Yanfang Ye, Ashley Ann Petersen, Austin Leitgeb, Saleh AlKhalifa, Kevin Minbiole, William M. Wuest, Amarda Shehu, Liang Zhao |
| 2022 | Multi-view Subspace Clustering on Topological Manifold. Shudong Huang, Hongjie Wu, Yazhou Ren, Ivor W. Tsang, Zenglin Xu, Wentao Feng, Jiancheng Lv |
| 2022 | MultiGuard: Provably Robust Multi-label Classification against Adversarial Examples. Jinyuan Jia, Wenjie Qu, Neil Zhenqiang Gong |
| 2022 | MultiScan: Scalable RGBD scanning for 3D environments with articulated objects. Yongsen Mao, Yiming Zhang, Hanxiao Jiang, Angel X. Chang, Manolis Savva |
| 2022 | Multiagent Q-learning with Sub-Team Coordination. Wenhan Huang, Kai Li, Kun Shao, Tianze Zhou, Matthew E. Taylor, Jun Luo, Dongge Wang, Hangyu Mao, Jianye Hao, Jun Wang, Xiaotie Deng |
| 2022 | Multiclass Learnability Beyond the PAC Framework: Universal Rates and Partial Concept Classes. Alkis Kalavasis, Grigoris Velegkas, Amin Karbasi |
| 2022 | Multilingual Abusive Comment Detection at Scale for Indic Languages. Vikram Gupta, Sumegh Roychowdhury, Mithun Das, Somnath Banerjee, Punyajoy Saha, Binny Mathew, Hastagiri Prakash Vanchinathan, Animesh Mukherjee |
| 2022 | Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts. Basil Mustafa, Carlos Riquelme, Joan Puigcerver, Rodolphe Jenatton, Neil Houlsby |
| 2022 | Multitasking Models are Robust to Structural Failure: A Neural Model for Bilingual Cognitive Reserve. Giannis Daras, Negin Raoof, Zoi Gkalitsiou, Alex Dimakis |
| 2022 | Multivariate Time-Series Forecasting with Temporal Polynomial Graph Neural Networks. Yijing Liu, Qinxian Liu, Jian-Wei Zhang, Haozhe Feng, Zhongwei Wang, Zihan Zhou, Wei Chen |
| 2022 | Multiview Human Body Reconstruction from Uncalibrated Cameras. Zhixuan Yu, Linguang Zhang, Yuanlu Xu, Chengcheng Tang, Luan Tran, Cem Keskin, Hyun Soo Park |
| 2022 | Museformer: Transformer with Fine- and Coarse-Grained Attention for Music Generation. Botao Yu, Peiling Lu, Rui Wang, Wei Hu, Xu Tan, Wei Ye, Shikun Zhang, Tao Qin, Tie-Yan Liu |
| 2022 | Mutual Information Divergence: A Unified Metric for Multimodal Generative Models. Jin-Hwa Kim, Yunji Kim, Jiyoung Lee, Kang Min Yoo, Sang-Woo Lee |
| 2022 | Myriad: a real-world testbed to bridge trajectory optimization and deep learning. Nikolaus H. R. Howe, Simon Dufort-Labbé, Nitarshan Rajkumar, Pierre-Luc Bacon |
| 2022 | M³ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design. Hanxue Liang, Zhiwen Fan, Rishov Sarkar, Ziyu Jiang, Tianlong Chen, Kai Zou, Yu Cheng, Cong Hao, Zhangyang Wang |
| 2022 | NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse Tasks. Renbo Tu, Nicholas Roberts, Mikhail Khodak, Junhong Shen, Frederic Sala, Ameet Talwalkar |
| 2022 | NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search. Yijian Qin, Ziwei Zhang, Xin Wang, Zeyang Zhang, Wenwu Zhu |
| 2022 | NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies. Arjun Krishnakumar, Colin White, Arber Zela, Renbo Tu, Mahmoud Safari, Frank Hutter |
| 2022 | NCP: Neural Correspondence Prior for Effective Unsupervised Shape Matching. Souhaib Attaiki, Maks Ovsjanikov |
| 2022 | NOMAD: Nonlinear Manifold Decoders for Operator Learning. Jacob H. Seidman, Georgios Kissas, Paris Perdikaris, George J. Pappas |
| 2022 | NOTE: Robust Continual Test-time Adaptation Against Temporal Correlation. Taesik Gong, Jongheon Jeong, Taewon Kim, Yewon Kim, Jinwoo Shin, Sung-Ju Lee |
| 2022 | NS3: Neuro-symbolic Semantic Code Search. Shushan Arakelyan, Anna Hakhverdyan, Miltiadis Allamanis, Luis Garcia, Christophe Hauser, Xiang Ren |
| 2022 | NSNet: A General Neural Probabilistic Framework for Satisfiability Problems. Zhaoyu Li, Xujie Si |
| 2022 | NUWA-Infinity: Autoregressive over Autoregressive Generation for Infinite Visual Synthesis. Jian Liang, Chenfei Wu, Xiaowei Hu, Zhe Gan, Jianfeng Wang, Lijuan Wang, Zicheng Liu, Yuejian Fang, Nan Duan |
| 2022 | Natural Color Fool: Towards Boosting Black-box Unrestricted Attacks. Shengming Yuan, Qilong Zhang, Lianli Gao, Yaya Cheng, Jingkuan Song |
| 2022 | Natural gradient enables fast sampling in spiking neural networks. Paul Masset, Jacob A. Zavatone-Veth, J. Patrick Connor, Venkatesh Murthy, Cengiz Pehlevan |
| 2022 | Natural image synthesis for the retina with variational information bottleneck representation. Babak Rahmani, Demetri Psaltis, Christophe Moser |
| 2022 | NaturalProver: Grounded Mathematical Proof Generation with Language Models. Sean Welleck, Jiacheng Liu, Ximing Lu, Hannaneh Hajishirzi, Yejin Choi |
| 2022 | Navigating Memory Construction by Global Pseudo-Task Simulation for Continual Learning. Yejia Liu, Wang Zhu, Shaolei Ren |
| 2022 | NeMF: Neural Motion Fields for Kinematic Animation. Chengan He, Jun Saito, James Zachary, Holly E. Rushmeier, Yi Zhou |
| 2022 | Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs. Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann |
| 2022 | Near-Isometric Properties of Kronecker-Structured Random Tensor Embeddings. Qijia Jiang |
| 2022 | Near-Optimal Collaborative Learning in Bandits. Clémence Réda, Sattar Vakili, Emilie Kaufmann |
| 2022 | Near-Optimal Correlation Clustering with Privacy. Vincent Cohen-Addad, Chenglin Fan, Silvio Lattanzi, Slobodan Mitrovic, Ashkan Norouzi-Fard, Nikos Parotsidis, Jakub Tarnawski |
| 2022 | Near-Optimal Goal-Oriented Reinforcement Learning in Non-Stationary Environments. Liyu Chen, Haipeng Luo |
| 2022 | Near-Optimal Multi-Agent Learning for Safe Coverage Control. Manish Prajapat, Matteo Turchetta, Melanie N. Zeilinger, Andreas Krause |
| 2022 | Near-Optimal No-Regret Learning Dynamics for General Convex Games. Gabriele Farina, Ioannis Anagnostides, Haipeng Luo, Chung-wei Lee, Christian Kroer, Tuomas Sandholm |
| 2022 | Near-Optimal Private and Scalable $k$-Clustering. Vincent Cohen-Addad, Alessandro Epasto, Vahab Mirrokni, Shyam Narayanan, Peilin Zhong |
| 2022 | Near-Optimal Randomized Exploration for Tabular Markov Decision Processes. Zhihan Xiong, Ruoqi Shen, Qiwen Cui, Maryam Fazel, Simon S. Du |
| 2022 | Near-Optimal Regret Bounds for Multi-batch Reinforcement Learning. Zihan Zhang, Yuhang Jiang, Yuan Zhou, Xiangyang Ji |
| 2022 | Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback. Tiancheng Jin, Tal Lancewicki, Haipeng Luo, Yishay Mansour, Aviv Rosenberg |
| 2022 | Near-Optimal Sample Complexity Bounds for Constrained MDPs. Sharan Vaswani, Lin Yang, Csaba Szepesvári |
| 2022 | Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions. Jiafan He, Dongruo Zhou, Tong Zhang, Quanquan Gu |
| 2022 | Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs. Shinji Ito, Taira Tsuchiya, Junya Honda |
| 2022 | Nearly-Tight Bounds for Testing Histogram Distributions. Clément L. Canonne, Ilias Diakonikolas, Daniel Kane, Sihan Liu |
| 2022 | NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning. Rongjun Qin, Xingyuan Zhang, Songyi Gao, Xiong-Hui Chen, Zewen Li, Weinan Zhang, Yang Yu |
| 2022 | Nest Your Adaptive Algorithm for Parameter-Agnostic Nonconvex Minimax Optimization. Junchi Yang, Xiang Li, Niao He |
| 2022 | Network change point localisation under local differential privacy. Mengchu Li, Thomas Berrett, Yi Yu |
| 2022 | NeuForm: Adaptive Overfitting for Neural Shape Editing. Connor Z. Lin, Niloy J. Mitra, Gordon Wetzstein, Leonidas J. Guibas, Paul Guerrero |
| 2022 | NeuPhysics: Editable Neural Geometry and Physics from Monocular Videos. Yi-Ling Qiao, Alexander Gao, Ming C. Lin |
| 2022 | Neur2SP: Neural Two-Stage Stochastic Programming. Rahul Patel, Justin Dumouchelle, Elias B. Khalil, Merve Bodur |
| 2022 | NeurOLight: A Physics-Agnostic Neural Operator Enabling Parametric Photonic Device Simulation. Jiaqi Gu, Zhengqi Gao, Chenghao Feng, Hanqing Zhu, Ray T. Chen, Duane S. Boning, David Z. Pan |
| 2022 | Neural Abstractions. Alessandro Abate, Alec Edwards, Mirco Giacobbe |
| 2022 | Neural Approximation of Graph Topological Features. Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen |
| 2022 | Neural Attentive Circuits. Martin Weiss, Nasim Rahaman, Francesco Locatello, Chris Pal, Yoshua Bengio, Bernhard Schölkopf, Li Erran Li, Nicolas Ballas |
| 2022 | Neural Basis Models for Interpretability. Filip Radenovic, Abhimanyu Dubey, Dhruv Mahajan |
| 2022 | Neural Circuit Architectural Priors for Embodied Control. Nikhil X. Bhattasali, Anthony M. Zador, Tatiana A. Engel |
| 2022 | Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold. Can Yaras, Peng Wang, Zhihui Zhu, Laura Balzano, Qing Qu |
| 2022 | Neural Conservation Laws: A Divergence-Free Perspective. Jack Richter-Powell, Yaron Lipman, Ricky T. Q. Chen |
| 2022 | Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules. Kazuki Irie, Francesco Faccio, Jürgen Schmidhuber |
| 2022 | Neural Estimation of Submodular Functions with Applications to Differentiable Subset Selection. Abir De, Soumen Chakrabarti |
| 2022 | Neural Lyapunov Control of Unknown Nonlinear Systems with Stability Guarantees. Ruikun Zhou, Thanin Quartz, Hans De Sterck, Jun Liu |
| 2022 | Neural Matching Fields: Implicit Representation of Matching Fields for Visual Correspondence. Sunghwan Hong, Jisu Nam, Seokju Cho, Susung Hong, Sangryul Jeon, Dongbo Min, Seungryong Kim |
| 2022 | Neural Network Architecture Beyond Width and Depth. Shijun Zhang, Zuowei Shen, Haizhao Yang |
| 2022 | Neural Payoff Machines: Predicting Fair and Stable Payoff Allocations Among Team Members. Daphne Cornelisse, Thomas Rood, Yoram Bachrach, Mateusz Malinowski, Tal Kachman |
| 2022 | Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions. Nikolaos Karalias, Joshua Robinson, Andreas Loukas, Stefanie Jegelka |
| 2022 | Neural Shape Deformation Priors. Jiapeng Tang, Lev Markhasin, Bi Wang, Justus Thies, Matthias Nießner |
| 2022 | Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs. Cristian Bodnar, Francesco Di Giovanni, Benjamin Paul Chamberlain, Pietro Lió, Michael M. Bronstein |
| 2022 | Neural Stochastic Control. Jingdong Zhang, Qunxi Zhu, Wei Lin |
| 2022 | Neural Stochastic PDEs: Resolution-Invariant Learning of Continuous Spatiotemporal Dynamics. Cristopher Salvi, Maud Lemercier, Andris Gerasimovics |
| 2022 | Neural Surface Reconstruction of Dynamic Scenes with Monocular RGB-D Camera. Hongrui Cai, Wanquan Feng, Xuetao Feng, Yan Wang, Juyong Zhang |
| 2022 | Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs. Ming Jin, Yuan-Fang Li, Shirui Pan |
| 2022 | Neural Topological Ordering for Computation Graphs. Mukul Gagrani, Corrado Rainone, Yang Yang, Harris Teague, Wonseok Jeon, Roberto Bondesan, Herke van Hoof, Christopher Lott, Weiliang Will Zeng, Piero Zappi |
| 2022 | Neural Transmitted Radiance Fields. Chengxuan Zhu, Renjie Wan, Boxin Shi |
| 2022 | Neural-Symbolic Entangled Framework for Complex Query Answering. Zezhong Xu, Wen Zhang, Peng Ye, Hui Chen, Huajun Chen |
| 2022 | NeuroSchedule: A Novel Effective GNN-based Scheduling Method for High-level Synthesis. Jun Zeng, Mingyang Kou, Hailong Yao |
| 2022 | Neuron with Steady Response Leads to Better Generalization. Qiang Fu, Lun Du, Haitao Mao, Xu Chen, Wei Fang, Shi Han, Dongmei Zhang |
| 2022 | Neurosymbolic Deep Generative Models for Sequence Data with Relational Constraints. Halley Young, Maxwell Du, Osbert Bastani |
| 2022 | New Definitions and Evaluations for Saliency Methods: Staying Intrinsic, Complete and Sound. Arushi Gupta, Nikunj Saunshi, Dingli Yu, Kaifeng Lyu, Sanjeev Arora |
| 2022 | New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma. Gautam Kamath, Argyris Mouzakis, Vikrant Singhal |
| 2022 | No Free Lunch from Deep Learning in Neuroscience: A Case Study through Models of the Entorhinal-Hippocampal Circuit. Rylan Schaeffer, Mikail Khona, Ila Fiete |
| 2022 | No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation. Yu-Guan Hsieh, Kimon Antonakopoulos, Volkan Cevher, Panayotis Mertikopoulos |
| 2022 | Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world. Eugene Vinitsky, Nathan Lichtlé, Xiaomeng Yang, Brandon Amos, Jakob N. Foerster |
| 2022 | NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification. Qitian Wu, Wentao Zhao, Zenan Li, David P. Wipf, Junchi Yan |
| 2022 | Noise Attention Learning: Enhancing Noise Robustness by Gradient Scaling. Yangdi Lu, Yang Bo, Wenbo He |
| 2022 | Non-Convex Bilevel Games with Critical Point Selection Maps. Michael Arbel, Julien Mairal |
| 2022 | Non-Gaussian Tensor Programs. Eugene A. Golikov, Greg Yang |
| 2022 | Non-Linear Coordination Graphs. Yipeng Kang, Tonghan Wang, Qianlan Yang, Xiaoran Wu, Chongjie Zhang |
| 2022 | Non-Linguistic Supervision for Contrastive Learning of Sentence Embeddings. Yiren Jian, Chongyang Gao, Soroush Vosoughi |
| 2022 | Non-Markovian Reward Modelling from Trajectory Labels via Interpretable Multiple Instance Learning. Joseph Early, Tom Bewley, Christine Evers, Sarvapali D. Ramchurn |
| 2022 | Non-Monotonic Latent Alignments for CTC-Based Non-Autoregressive Machine Translation. Chenze Shao, Yang Feng |
| 2022 | Non-Stationary Bandits under Recharging Payoffs: Improved Planning with Sublinear Regret. Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai |
| 2022 | Non-convex online learning via algorithmic equivalence. Udaya Ghai, Zhou Lu, Elad Hazan |
| 2022 | Non-deep Networks. Ankit Goyal, Alexey Bochkovskiy, Jia Deng, Vladlen Koltun |
| 2022 | Non-identifiability and the Blessings of Misspecification in Models of Molecular Fitness. Eli N. Weinstein, Alan Nawzad Amin, Jonathan Frazer, Debora S. Marks |
| 2022 | Non-monotonic Resource Utilization in the Bandits with Knapsacks Problem. Raunak Kumar, Robert Kleinberg |
| 2022 | Non-rigid Point Cloud Registration with Neural Deformation Pyramid. Yang Li, Tatsuya Harada |
| 2022 | Non-stationary Bandits with Knapsacks. Shang Liu, Jiashuo Jiang, Xiaocheng Li |
| 2022 | Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting. Yong Liu, Haixu Wu, Jianmin Wang, Mingsheng Long |
| 2022 | Nonlinear MCMC for Bayesian Machine Learning. James Vuckovic |
| 2022 | Nonlinear Sufficient Dimension Reduction with a Stochastic Neural Network. Siqi Liang, Yan Sun, Faming Liang |
| 2022 | Nonnegative Tensor Completion via Integer Optimization. Caleb Bugg, Chen Chen, Anil Aswani |
| 2022 | Nonparametric Uncertainty Quantification for Single Deterministic Neural Network. Nikita Kotelevskii, Aleksandr Artemenkov, Kirill Fedyanin, Fedor Noskov, Alexander Fishkov, Artem Shelmanov, Artem Vazhentsev, Aleksandr Petiushko, Maxim Panov |
| 2022 | Nonstationary Dual Averaging and Online Fair Allocation. Luofeng Liao, Yuan Gao, Christian Kroer |
| 2022 | Normalizing Flows for Knockoff-free Controlled Feature Selection. Derek Hansen, Brian Manzo, Jeffrey Regier |
| 2022 | Not All Bits have Equal Value: Heterogeneous Precisions via Trainable Noise. Pedro Savarese, Xin Yuan, Yanjing Li, Michael Maire |
| 2022 | Not too little, not too much: a theoretical analysis of graph (over)smoothing. Nicolas Keriven |
| 2022 | OGC: Unsupervised 3D Object Segmentation from Rigid Dynamics of Point Clouds. Ziyang Song, Bo Yang |
| 2022 | OLIVES Dataset: Ophthalmic Labels for Investigating Visual Eye Semantics. Mohit Prabhushankar, Kiran Kokilepersaud, Yash-Yee Logan, Stephanie Trejo Corona, Ghassan AlRegib, Charles C. Wykoff |
| 2022 | OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs. Yangze Zhou, Gitta Kutyniok, Bruno Ribeiro |
| 2022 | OPEN: Orthogonal Propagation with Ego-Network Modeling. Liang Yang, Lina Kang, Qiuliang Zhang, Mengzhe Li, Bingxin Niu, Dongxiao He, Zhen Wang, Chuan Wang, Xiaochun Cao, Yuanfang Guo |
| 2022 | ORIENT: Submodular Mutual Information Measures for Data Subset Selection under Distribution Shift. Athresh Karanam, Krishnateja Killamsetty, Harsha Kokel, Rishabh K. Iyer |
| 2022 | OST: Improving Generalization of DeepFake Detection via One-Shot Test-Time Training. Liang Chen, Yong Zhang, Yibing Song, Jue Wang, Lingqiao Liu |
| 2022 | OTKGE: Multi-modal Knowledge Graph Embeddings via Optimal Transport. Zongsheng Cao, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang |
| 2022 | Obj2Seq: Formatting Objects as Sequences with Class Prompt for Visual Tasks. Zhiyang Chen, Yousong Zhu, Zhaowen Li, Fan Yang, Wei Li, Haixin Wang, Chaoyang Zhao, Liwei Wu, Rui Zhao, Jinqiao Wang, Ming Tang |
| 2022 | Object Representations as Fixed Points: Training Iterative Refinement Algorithms with Implicit Differentiation. Michael Chang, Tom Griffiths, Sergey Levine |
| 2022 | Object Scene Representation Transformer. Mehdi S. M. Sajjadi, Daniel Duckworth, Aravindh Mahendran, Sjoerd van Steenkiste, Filip Pavetic, Mario Lucic, Leonidas J. Guibas, Klaus Greff, Thomas Kipf |
| 2022 | Object-Category Aware Reinforcement Learning. Qi Yi, Rui Zhang, Shaohui Peng, Jiaming Guo, Xing Hu, Zidong Du, Xishan Zhang, Qi Guo, Yunji Chen |
| 2022 | OccGen: Selection of Real-world Multilingual Parallel Data Balanced in Gender within Occupations. Marta R. Costa-jussà, Christine Basta, Oriol Domingo, André Rubungo |
| 2022 | Off-Policy Evaluation for Action-Dependent Non-stationary Environments. Yash Chandak, Shiv Shankar, Nathaniel D. Bastian, Bruno C. da Silva, Emma Brunskill, Philip S. Thomas |
| 2022 | Off-Policy Evaluation for Episodic Partially Observable Markov Decision Processes under Non-Parametric Models. Rui Miao, Zhengling Qi, Xiaoke Zhang |
| 2022 | Off-Policy Evaluation with Deficient Support Using Side Information. Nicolò Felicioni, Maurizio Ferrari Dacrema, Marcello Restelli, Paolo Cremonesi |
| 2022 | Off-Policy Evaluation with Policy-Dependent Optimization Response. Wenshuo Guo, Michael I. Jordan, Angela Zhou |
| 2022 | Off-Team Learning. Brandon Cui, Hengyuan Hu, Andrei Lupu, Samuel Sokota, Jakob N. Foerster |
| 2022 | Offline Goal-Conditioned Reinforcement Learning via $f$-Advantage Regression. Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani |
| 2022 | Offline Multi-Agent Reinforcement Learning with Knowledge Distillation. Wei-Cheng Tseng, Tsun-Hsuan Johnson Wang, Yen-Chen Lin, Phillip Isola |
| 2022 | Okapi: Generalising Better by Making Statistical Matches Match. Myles Bartlett, Sara Romiti, Viktoriia Sharmanska, Novi Quadrianto |
| 2022 | Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again. Ajay Jaiswal, Peihao Wang, Tianlong Chen, Justin F. Rousseau, Ying Ding, Zhangyang Wang |
| 2022 | OmniVL: One Foundation Model for Image-Language and Video-Language Tasks. Junke Wang, Dongdong Chen, Zuxuan Wu, Chong Luo, Luowei Zhou, Yucheng Zhao, Yujia Xie, Ce Liu, Yu-Gang Jiang, Lu Yuan |
| 2022 | On A Mallows-type Model For (Ranked) Choices. Yifan Feng, Yuxuan Tang |
| 2022 | On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models. Kamil Deja, Anna Kuzina, Tomasz Trzcinski, Jakub M. Tomczak |
| 2022 | On Batch Teaching with Sample Complexity Bounded by VCD. Farnam Mansouri, Hans Simon, Adish Singla, Sandra Zilles |
| 2022 | On Computing Probabilistic Explanations for Decision Trees. Marcelo Arenas, Pablo Barceló, Miguel A. Romero Orth, Bernardo Subercaseaux |
| 2022 | On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond. Xiaotong Yuan, Ping Li |
| 2022 | On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds. Biraj Dahal, Alexander Havrilla, Minshuo Chen, Tuo Zhao, Wenjing Liao |
| 2022 | On Divergence Measures for Bayesian Pseudocoresets. Balhae Kim, Jungwon Choi, Seanie Lee, Yoonho Lee, Jung-Woo Ha, Juho Lee |
| 2022 | On Efficient Online Imitation Learning via Classification. Yichen Li, Chicheng Zhang |
| 2022 | On Elimination Strategies for Bandit Fixed-Confidence Identification. Andrea Tirinzoni, Rémy Degenne |
| 2022 | On Embeddings for Numerical Features in Tabular Deep Learning. Yury Gorishniy, Ivan Rubachev, Artem Babenko |
| 2022 | On Enforcing Better Conditioned Meta-Learning for Rapid Few-Shot Adaptation. Markus Hiller, Mehrtash Harandi, Tom Drummond |
| 2022 | On Feature Learning in the Presence of Spurious Correlations. Pavel Izmailov, Polina Kirichenko, Nate Gruver, Andrew Gordon Wilson |
| 2022 | On Gap-dependent Bounds for Offline Reinforcement Learning. Xinqi Wang, Qiwen Cui, Simon S. Du |
| 2022 | On Image Segmentation With Noisy Labels: Characterization and Volume Properties of the Optimal Solutions to Accuracy and Dice. Marcus Nordström, Henrik Hult, Fredrik Löfman, Jonas Söderberg |
| 2022 | On Infinite Separations Between Simple and Optimal Mechanisms. Alexandros Psomas, Ariel Schvartzman, S. Matthew Weinberg |
| 2022 | On Kernelized Multi-Armed Bandits with Constraints. Xingyu Zhou, Bo Ji |
| 2022 | On Learning Fairness and Accuracy on Multiple Subgroups. Changjian Shui, Gezheng Xu, Qi Chen, Jiaqi Li, Charles X. Ling, Tal Arbel, Boyu Wang, Christian Gagné |
| 2022 | On Learning and Refutation in Noninteractive Local Differential Privacy. Alexander Edmonds, Aleksandar Nikolov, Toniann Pitassi |
| 2022 | On Leave-One-Out Conditional Mutual Information For Generalization. Mohamad Rida Rammal, Alessandro Achille, Aditya Golatkar, Suhas N. Diggavi, Stefano Soatto |
| 2022 | On Margin Maximization in Linear and ReLU Networks. Gal Vardi, Ohad Shamir, Nati Srebro |
| 2022 | On Margins and Generalisation for Voting Classifiers. Felix Biggs, Valentina Zantedeschi, Benjamin Guedj |
| 2022 | On Measuring Excess Capacity in Neural Networks. Florian Graf, Sebastian Zeng, Bastian Rieck, Marc Niethammer, Roland Kwitt |
| 2022 | On Non-Linear operators for Geometric Deep Learning. Grégoire Sergeant-Perthuis, Jakob Maier, Joan Bruna, Edouard Oyallon |
| 2022 | On Optimal Learning Under Targeted Data Poisoning. Steve Hanneke, Amin Karbasi, Mohammad Mahmoody, Idan Mehalel, Shay Moran |
| 2022 | On Privacy and Personalization in Cross-Silo Federated Learning. Ken Ziyu Liu, Shengyuan Hu, Steven Wu, Virginia Smith |
| 2022 | On Reinforcement Learning and Distribution Matching for Fine-Tuning Language Models with no Catastrophic Forgetting. Tomasz Korbak, Hady Elsahar, Germán Kruszewski, Marc Dymetman |
| 2022 | On Robust Multiclass Learnability. Jingyuan Xu, Weiwei Liu |
| 2022 | On Sample Optimality in Personalized Collaborative and Federated Learning. Mathieu Even, Laurent Massoulié, Kevin Scaman |
| 2022 | On Scalable Testing of Samplers. Yash Pote, Kuldeep S. Meel |
| 2022 | On Scrambling Phenomena for Randomly Initialized Recurrent Networks. Vaggos Chatziafratis, Ioannis Panageas, Clayton Sanford, Stelios Stavroulakis |
| 2022 | On Translation and Reconstruction Guarantees of the Cycle-Consistent Generative Adversarial Networks. Anish Chakrabarty, Swagatam Das |
| 2022 | On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification. Sanyam Kapoor, Wesley J. Maddox, Pavel Izmailov, Andrew Gordon Wilson |
| 2022 | On global convergence of ResNets: From finite to infinite width using linear parameterization. Raphaël Barboni, Gabriel Peyré, François-Xavier Vialard |
| 2022 | On the Adversarial Robustness of Mixture of Experts. Joan Puigcerver, Rodolphe Jenatton, Carlos Riquelme, Pranjal Awasthi, Srinadh Bhojanapalli |
| 2022 | On the Complexity of Adversarial Decision Making. Dylan J. Foster, Alexander Rakhlin, Ayush Sekhari, Karthik Sridharan |
| 2022 | On the Convergence Theory for Hessian-Free Bilevel Algorithms. Daouda Sow, Kaiyi Ji, Yingbin Liang |
| 2022 | On the Convergence of Stochastic Multi-Objective Gradient Manipulation and Beyond. Shiji Zhou, Wenpeng Zhang, Jiyan Jiang, Wenliang Zhong, Jinjie Gu, Wenwu Zhu |
| 2022 | On the Discrimination Risk of Mean Aggregation Feature Imputation in Graphs. Arjun Subramonian, Kai-Wei Chang, Yizhou Sun |
| 2022 | On the Double Descent of Random Features Models Trained with SGD. Fanghui Liu, Johan A. K. Suykens, Volkan Cevher |
| 2022 | On the Effect of Pre-training for Transformer in Different Modality on Offline Reinforcement Learning. Shiro Takagi |
| 2022 | On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias. Itay Safran, Gal Vardi, Jason D. Lee |
| 2022 | On the Effectiveness of Fine-tuning Versus Meta-reinforcement Learning. Mandi Zhao, Pieter Abbeel, Stephen James |
| 2022 | On the Effectiveness of Lipschitz-Driven Rehearsal in Continual Learning. Lorenzo Bonicelli, Matteo Boschini, Angelo Porrello, Concetto Spampinato, Simone Calderara |
| 2022 | On the Effectiveness of Persistent Homology. Renata Turkes, Guido F. Montúfar, Nina Otter |
| 2022 | On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood. Moses Charikar, Zhihao Jiang, Kirankumar Shiragur, Aaron Sidford |
| 2022 | On the Epistemic Limits of Personalized Prediction. Lucas Monteiro Paes, Carol Xuan Long, Berk Ustun, Flávio P. Calmon |
| 2022 | On the Frequency-bias of Coordinate-MLPs. Sameera Ramasinghe, Lachlan E. MacDonald, Simon Lucey |
| 2022 | On the Generalizability and Predictability of Recommender Systems. Duncan C. McElfresh, Sujay Khandagale, Jonathan Valverde, John Dickerson, Colin White |
| 2022 | On the Generalization Power of the Overfitted Three-Layer Neural Tangent Kernel Model. Peizhong Ju, Xiaojun Lin, Ness B. Shroff |
| 2022 | On the Global Convergence Rates of Decentralized Softmax Gradient Play in Markov Potential Games. Runyu Zhang, Jincheng Mei, Bo Dai, Dale Schuurmans, Na Li |
| 2022 | On the Identifiability of Nonlinear ICA: Sparsity and Beyond. Yujia Zheng, Ignavier Ng, Kun Zhang |
| 2022 | On the Importance of Gradient Norm in PAC-Bayesian Bounds. Itai Gat, Yossi Adi, Alexander G. Schwing, Tamir Hazan |
| 2022 | On the Interpretability of Regularisation for Neural Networks Through Model Gradient Similarity. Vincent Szolnoky, Viktor Andersson, Balázs Kulcsár, Rebecka Jörnsten |
| 2022 | On the Learning Mechanisms in Physical Reasoning. Shiqian Li, Kewen Wu, Chi Zhang, Yixin Zhu |
| 2022 | On the Limitations of Stochastic Pre-processing Defenses. Yue Gao, Ilia Shumailov, Kassem Fawaz, Nicolas Papernot |
| 2022 | On the Parameterization and Initialization of Diagonal State Space Models. Albert Gu, Karan Goel, Ankit Gupta, Christopher Ré |
| 2022 | On the Representation Collapse of Sparse Mixture of Experts. Zewen Chi, Li Dong, Shaohan Huang, Damai Dai, Shuming Ma, Barun Patra, Saksham Singhal, Payal Bajaj, Xia Song, Xian-Ling Mao, Heyan Huang, Furu Wei |
| 2022 | On the Robustness of Deep Clustering Models: Adversarial Attacks and Defenses. Anshuman Chhabra, Ashwin Sekhari, Prasant Mohapatra |
| 2022 | On the Robustness of Graph Neural Diffusion to Topology Perturbations. Yang Song, Qiyu Kang, Sijie Wang, Kai Zhao, Wee Peng Tay |
| 2022 | On the SDEs and Scaling Rules for Adaptive Gradient Algorithms. Sadhika Malladi, Kaifeng Lyu, Abhishek Panigrahi, Sanjeev Arora |
| 2022 | On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach. Dennis Wei, Rahul Nair, Amit Dhurandhar, Kush R. Varshney, Elizabeth Daly, Moninder Singh |
| 2022 | On the Sample Complexity of Stabilizing LTI Systems on a Single Trajectory. Yang Hu, Adam Wierman, Guannan Qu |
| 2022 | On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels. Amnon Geifman, Meirav Galun, David Jacobs, Ronen Basri |
| 2022 | On the Stability and Scalability of Node Perturbation Learning. Naoki Hiratani, Yash Mehta, Timothy P. Lillicrap, Peter E. Latham |
| 2022 | On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL. Jinglin Chen, Aditya Modi, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal |
| 2022 | On the Strong Correlation Between Model Invariance and Generalization. Weijian Deng, Stephen Gould, Liang Zheng |
| 2022 | On the Symmetries of Deep Learning Models and their Internal Representations. Charles Godfrey, Davis Brown, Tegan Emerson, Henry Kvinge |
| 2022 | On the Theoretical Properties of Noise Correlation in Stochastic Optimization. Aurélien Lucchi, Frank Proske, Antonio Orvieto, Francis R. Bach, Hans Kersting |
| 2022 | On the Tradeoff Between Robustness and Fairness. Xinsong Ma, Zekai Wang, Weiwei Liu |
| 2022 | On the consistent estimation of optimal Receiver Operating Characteristic (ROC) curve. Renxiong Liu, Yunzhang Zhu |
| 2022 | On the convergence of policy gradient methods to Nash equilibria in general stochastic games. Angeliki Giannou, Kyriakos Lotidis, Panayotis Mertikopoulos, Emmanouil V. Vlatakis-Gkaragkounis |
| 2022 | On the detrimental effect of invariances in the likelihood for variational inference. Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus |
| 2022 | On the difficulty of learning chaotic dynamics with RNNs. Jonas M. Mikhaeil, Zahra Monfared, Daniel Durstewitz |
| 2022 | On the generalization of learning algorithms that do not converge. Nisha Chandramoorthy, Andreas Loukas, Khashayar Gatmiry, Stefanie Jegelka |
| 2022 | On the inability of Gaussian process regression to optimally learn compositional functions. Matteo Giordano, Kolyan Ray, Johannes Schmidt-Hieber |
| 2022 | On the non-universality of deep learning: quantifying the cost of symmetry. Emmanuel Abbe, Enric Boix-Adserà |
| 2022 | On the relationship between variational inference and auto-associative memory. Louis Annabi, Alexandre Pitti, Mathias Quoy |
| 2022 | On the role of overparameterization in off-policy Temporal Difference learning with linear function approximation. Valentin Thomas |
| 2022 | On the symmetries of the synchronization problem in Cryo-EM: Multi-Frequency Vector Diffusion Maps on the Projective Plane. Gabriele Cesa, Arash Behboodi, Taco S. Cohen, Max Welling |
| 2022 | On-Demand Sampling: Learning Optimally from Multiple Distributions. Nika Haghtalab, Michael I. Jordan, Eric Zhao |
| 2022 | On-Device Training Under 256KB Memory. Ji Lin, Ligeng Zhu, Wei-Ming Chen, Wei-Chen Wang, Chuang Gan, Song Han |
| 2022 | One Model to Edit Them All: Free-Form Text-Driven Image Manipulation with Semantic Modulations. Yiming Zhu, Hongyu Liu, Yibing Song, Ziyang Yuan, Xintong Han, Chun Yuan, Qifeng Chen, Jue Wang |
| 2022 | One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement. Ning Xu, Congyu Qiao, Jiaqi Lv, Xin Geng, Min-Ling Zhang |
| 2022 | One for All: Simultaneous Metric and Preference Learning over Multiple Users. Gregory Canal, Blake Mason, Ramya Korlakai Vinayak, Robert Nowak |
| 2022 | One-Inlier is First: Towards Efficient Position Encoding for Point Cloud Registration. Fan Yang, Lin Guo, Zhi Chen, Wenbing Tao |
| 2022 | One-shot Neural Backdoor Erasing via Adversarial Weight Masking. Shuwen Chai, Jinghui Chen |
| 2022 | OnePose++: Keypoint-Free One-Shot Object Pose Estimation without CAD Models. Xingyi He, Jiaming Sun, Yuang Wang, Di Huang, Hujun Bao, Xiaowei Zhou |
| 2022 | Online Agnostic Multiclass Boosting. Vinod Raman, Ambuj Tewari |
| 2022 | Online Algorithms for the Santa Claus Problem. Max Springer, MohammadTaghi Hajiaghayi, Debmalya Panigrahi, Mohammad Reza Khani |
| 2022 | Online Allocation and Learning in the Presence of Strategic Agents. Steven Yin, Shipra Agrawal, Assaf Zeevi |
| 2022 | Online Bipartite Matching with Advice: Tight Robustness-Consistency Tradeoffs for the Two-Stage Model. Billy Jin, Will Ma |
| 2022 | Online Convex Optimization with Hard Constraints: Towards the Best of Two Worlds and Beyond. Hengquan Guo, Xin Liu, Honghao Wei, Lei Ying |
| 2022 | Online Decision Mediation. Daniel Jarrett, Alihan Hüyük, Mihaela van der Schaar |
| 2022 | Online Deep Equilibrium Learning for Regularization by Denoising. Jiaming Liu, Xiaojian Xu, Weijie Gan, Shirin Shoushtari, Ulugbek Kamilov |
| 2022 | Online Frank-Wolfe with Arbitrary Delays. Yuanyu Wan, Wei-Wei Tu, Lijun Zhang |
| 2022 | Online Learning and Pricing for Network Revenue Management with Reusable Resources. Huiwen Jia, Cong Shi, Siqian Shen |
| 2022 | Online Minimax Multiobjective Optimization: Multicalibeating and Other Applications. Daniel Lee, Georgy Noarov, Mallesh M. Pai, Aaron Roth |
| 2022 | Online Neural Sequence Detection with Hierarchical Dirichlet Point Process. Weihan Li, Yu Qi, Gang Pan |
| 2022 | Online PAC-Bayes Learning. Maxime Haddouche, Benjamin Guedj |
| 2022 | Online Reinforcement Learning for Mixed Policy Scopes. Junzhe Zhang, Elias Bareinboim |
| 2022 | Online Training Through Time for Spiking Neural Networks. Mingqing Xiao, Qingyan Meng, Zongpeng Zhang, Di He, Zhouchen Lin |
| 2022 | Ontologue: Declarative Benchmark Construction for Ontological Multi-Label Classification. Sean Yang, Bernease Herman, Bill Howe |
| 2022 | Open High-Resolution Satellite Imagery: The WorldStrat Dataset - With Application to Super-Resolution. Julien Cornebise, Ivan Orsolic, Freddie Kalaitzis |
| 2022 | Open-Ended Reinforcement Learning with Neural Reward Functions. Robert Meier, Asier Mujika |
| 2022 | OpenAUC: Towards AUC-Oriented Open-Set Recognition. Zitai Wang, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang |
| 2022 | OpenFWI: Large-scale Multi-structural Benchmark Datasets for Full Waveform Inversion. Chengyuan Deng, Shihang Feng, Hanchen Wang, Xitong Zhang, Peng Jin, Yinan Feng, Qili Zeng, Yinpeng Chen, Youzuo Lin |
| 2022 | OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters. Piera Riccio, Bill Psomas, Francesco Galati, Francisco Escolano, Thomas Hofmann, Nuria Oliver |
| 2022 | OpenOOD: Benchmarking Generalized Out-of-Distribution Detection. Jingkang Yang, Pengyun Wang, Dejian Zou, Zitang Zhou, Kunyuan Ding, Wenxuan Peng, Haoqi Wang, Guangyao Chen, Bo Li, Yiyou Sun, Xuefeng Du, Kaiyang Zhou, Wayne Zhang, Dan Hendrycks, Yixuan Li, Ziwei Liu |
| 2022 | OpenSRH: optimizing brain tumor surgery using intraoperative stimulated Raman histology. Cheng Jiang, Asadur Chowdury, Xinhai Hou, Akhil Kondepudi, Christian W. Freudiger, Kyle Conway, Sandra Camelo-Piragua, Daniel A. Orringer, Honglak Lee, Todd C. Hollon |
| 2022 | OpenXAI: Towards a Transparent Evaluation of Model Explanations. Chirag Agarwal, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, Himabindu Lakkaraju |
| 2022 | Operative dimensions in unconstrained connectivity of recurrent neural networks. Renate Krause, Matthew Cook, Sepp Kollmorgen, Valerio Mante, Giacomo Indiveri |
| 2022 | Operator Splitting Value Iteration. Amin Rakhsha, Andrew Wang, Mohammad Ghavamzadeh, Amir-massoud Farahmand |
| 2022 | Optimal Algorithms for Decentralized Stochastic Variational Inequalities. Dmitry Kovalev, Aleksandr Beznosikov, Abdurakhmon Sadiev, Michael Persiianov, Peter Richtárik, Alexander V. Gasnikov |
| 2022 | Optimal Binary Classification Beyond Accuracy. Shashank Singh, Justin T. Khim |
| 2022 | Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning. Elias Frantar, Dan Alistarh |
| 2022 | Optimal Comparator Adaptive Online Learning with Switching Cost. Zhiyu Zhang, Ashok Cutkosky, Yannis Paschalidis |
| 2022 | Optimal Dynamic Regret in LQR Control. Dheeraj Baby, Yu-Xiang Wang |
| 2022 | Optimal Efficiency-Envy Trade-Off via Optimal Transport. Steven Yin, Christian Kroer |
| 2022 | Optimal Gradient Sliding and its Application to Optimal Distributed Optimization Under Similarity. Dmitry Kovalev, Aleksandr Beznosikov, Ekaterina Borodich, Alexander V. Gasnikov, Gesualdo Scutari |
| 2022 | Optimal Positive Generation via Latent Transformation for Contrastive Learning. Yinqi Li, Hong Chang, Bingpeng Ma, Shiguang Shan, Xilin Chen |
| 2022 | Optimal Query Complexities for Dynamic Trace Estimation. David P. Woodruff, Fred Zhang, Richard Zhang |
| 2022 | Optimal Rates for Regularized Conditional Mean Embedding Learning. Zhu Li, Dimitri Meunier, Mattes Mollenhauer, Arthur Gretton |
| 2022 | Optimal Scaling for Locally Balanced Proposals in Discrete Spaces. Haoran Sun, Hanjun Dai, Dale Schuurmans |
| 2022 | Optimal Transport of Classifiers to Fairness. Maarten Buyl, Tijl De Bie |
| 2022 | Optimal Transport-based Identity Matching for Identity-invariant Facial Expression Recognition. Dae Ha Kim, Byung Cheol Song |
| 2022 | Optimal Weak to Strong Learning. Kasper Green Larsen, Martin Ritzert |
| 2022 | Optimal and Adaptive Monteiro-Svaiter Acceleration. Yair Carmon, Danielle Hausler, Arun Jambulapati, Yujia Jin, Aaron Sidford |
| 2022 | Optimal-er Auctions through Attention. Dmitry Ivanov, Iskander Safiulin, Igor Filippov, Ksenia Balabaeva |
| 2022 | Optimistic Mirror Descent Either Converges to Nash or to Strong Coarse Correlated Equilibria in Bimatrix Games. Ioannis Anagnostides, Gabriele Farina, Ioannis Panageas, Tuomas Sandholm |
| 2022 | Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees. Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Mark Rowland, Michal Valko, Pierre Ménard |
| 2022 | Optimistic Tree Searches for Combinatorial Black-Box Optimization. Cédric Malherbe, Antoine Grosnit, Rasul Tutunov, Haitham Bou-Ammar, Jun Wang |
| 2022 | Optimizing Data Collection for Machine Learning. Rafid Mahmood, James Lucas, José M. Álvarez, Sanja Fidler, Marc T. Law |
| 2022 | Optimizing Relevance Maps of Vision Transformers Improves Robustness. Hila Chefer, Idan Schwartz, Lior Wolf |
| 2022 | Oracle Inequalities for Model Selection in Offline Reinforcement Learning. Jonathan N. Lee, George Tucker, Ofir Nachum, Bo Dai, Emma Brunskill |
| 2022 | Oracle-Efficient Online Learning for Smoothed Adversaries. Nika Haghtalab, Yanjun Han, Abhishek Shetty, Kunhe Yang |
| 2022 | Order-Invariant Cardinality Estimators Are Differentially Private. Charlie Dickens, Justin Thaler, Daniel Ting |
| 2022 | Ordered Subgraph Aggregation Networks. Chendi Qian, Gaurav Rattan, Floris Geerts, Mathias Niepert, Christopher Morris |
| 2022 | OrdinalCLIP: Learning Rank Prompts for Language-Guided Ordinal Regression. Wanhua Li, Xiaoke Huang, Zheng Zhu, Yansong Tang, Xiu Li, Jie Zhou, Jiwen Lu |
| 2022 | Orthogonal Transformer: An Efficient Vision Transformer Backbone with Token Orthogonalization. Huaibo Huang, Xiaoqiang Zhou, Ran He |
| 2022 | Oscillatory Tracking of Continuous Attractor Neural Networks Account for Phase Precession and Procession of Hippocampal Place Cells. Tianhao Chu, Zilong Ji, Junfeng Zuo, Wenhao Zhang, Tiejun Huang, Yuanyuan Mi, Si Wu |
| 2022 | Out-of-Distribution Detection via Conditional Kernel Independence Model. Yu Wang, Jingjing Zou, Jingyang Lin, Qing Ling, Yingwei Pan, Ting Yao, Tao Mei |
| 2022 | Out-of-Distribution Detection with An Adaptive Likelihood Ratio on Informative Hierarchical VAE. Yewen Li, Chaojie Wang, Xiaobo Xia, Tongliang Liu, Xin Miao, Bo An |
| 2022 | Outlier Suppression: Pushing the Limit of Low-bit Transformer Language Models. Xiuying Wei, Yunchen Zhang, Xiangguo Zhang, Ruihao Gong, Shanghang Zhang, Qi Zhang, Fengwei Yu, Xianglong Liu |
| 2022 | Outlier-Robust Sparse Estimation via Non-Convex Optimization. Yu Cheng, Ilias Diakonikolas, Rong Ge, Shivam Gupta, Daniel Kane, Mahdi Soltanolkotabi |
| 2022 | Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions. Ilias Diakonikolas, Daniel Kane, Jasper C. H. Lee, Ankit Pensia |
| 2022 | Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling. Junyuan Hong, Lingjuan Lyu, Jiayu Zhou, Michael Spranger |
| 2022 | Overparameterization from Computational Constraints. Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Mingyuan Wang |
| 2022 | P2P: Tuning Pre-trained Image Models for Point Cloud Analysis with Point-to-Pixel Prompting. Ziyi Wang, Xumin Yu, Yongming Rao, Jie Zhou, Jiwen Lu |
| 2022 | PAC Prediction Sets for Meta-Learning. Sangdon Park, Edgar Dobriban, Insup Lee, Osbert Bastani |
| 2022 | PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization. Sanae Lotfi, Marc Finzi, Sanyam Kapoor, Andres Potapczynski, Micah Goldblum, Andrew Gordon Wilson |
| 2022 | PAC: Assisted Value Factorization with Counterfactual Predictions in Multi-Agent Reinforcement Learning. Hanhan Zhou, Tian Lan, Vaneet Aggarwal |
| 2022 | PALBERT: Teaching ALBERT to Ponder. Nikita Balagansky, Daniil Gavrilov |
| 2022 | PALMER: Perception - Action Loop with Memory for Long-Horizon Planning. Onur Beker, Mohammad Mohammadi, Amir Zamir |
| 2022 | PDEBench: An Extensive Benchmark for Scientific Machine Learning. Makoto Takamoto, Timothy Praditia, Raphael Leiteritz, Daniel MacKinlay, Francesco Alesiani, Dirk Pflüger, Mathias Niepert |
| 2022 | PDSketch: Integrated Domain Programming, Learning, and Planning. Jiayuan Mao, Tomás Lozano-Pérez, Josh Tenenbaum, Leslie Pack Kaelbling |
| 2022 | PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding. Minghao Xu, Zuobai Zhang, Jiarui Lu, Zhaocheng Zhu, Yangtian Zhang, Chang Ma, Runcheng Liu, Jian Tang |
| 2022 | PKD: General Distillation Framework for Object Detectors via Pearson Correlation Coefficient. Weihan Cao, Yifan Zhang, Jianfei Gao, Anda Cheng, Ke Cheng, Jian Cheng |
| 2022 | PROSPECT: Labeled Tandem Mass Spectrometry Dataset for Machine Learning in Proteomics. Omar Shouman, Wassim Gabriel, Victor-George Giurcoiu, Vitor Sternlicht, Mathias Wilhelm |
| 2022 | PaCo: Parameter-Compositional Multi-task Reinforcement Learning. Lingfeng Sun, Haichao Zhang, Wei Xu, Masayoshi Tomizuka |
| 2022 | Palm up: Playing in the Latent Manifold for Unsupervised Pretraining. Hao Liu, Tom Zahavy, Volodymyr Mnih, Satinder Singh |
| 2022 | Panchromatic and Multispectral Image Fusion via Alternating Reverse Filtering Network. Keyu Yan, Man Zhou, Jie Huang, Feng Zhao, Chengjun Xie, Chongyi Li, Danfeng Hong |
| 2022 | Para-CFlows: $C^k$-universal diffeomorphism approximators as superior neural surrogates. Junlong Lyu, Zhitang Chen, Chang Feng, Wenjing Cun, Shengyu Zhu, Yanhui Geng, Zhijie Xu, Chen Yongwei |
| 2022 | Parallel Tempering With a Variational Reference. Nikola Surjanovic, Saifuddin Syed, Alexandre Bouchard-Côté, Trevor Campbell |
| 2022 | Parameter tuning and model selection in Optimal Transport with semi-dual Brenier formulation. Adrien Vacher, François-Xavier Vialard |
| 2022 | Parameter-Efficient Masking Networks. Yue Bai, Huan Wang, Xu Ma, Yitian Zhang, Zhiqiang Tao, Yun Fu |
| 2022 | Parameter-free Dynamic Graph Embedding for Link Prediction. Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Ning Gu |
| 2022 | Parameter-free Regret in High Probability with Heavy Tails. Jiujia Zhang, Ashok Cutkosky |
| 2022 | Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference. Jasper Tan, Blake Mason, Hamid Javadi, Richard G. Baraniuk |
| 2022 | Parametrically Retargetable Decision-Makers Tend To Seek Power. Alexander Matt Turner, Prasad Tadepalli |
| 2022 | Paraphrasing Is All You Need for Novel Object Captioning. Cheng-Fu Yang, Yao-Hung Hubert Tsai, Wan-Cyuan Fan, Russ Salakhutdinov, Louis-Philippe Morency, Frank Wang |
| 2022 | Pareto Set Learning for Expensive Multi-Objective Optimization. Xi Lin, Zhiyuan Yang, Xiaoyuan Zhang, Qingfu Zhang |
| 2022 | Partial Identification of Treatment Effects with Implicit Generative Models. Vahid Balazadeh Meresht, Vasilis Syrgkanis, Rahul G. Krishnan |
| 2022 | PatchComplete: Learning Multi-Resolution Patch Priors for 3D Shape Completion on Unseen Categories. Yuchen Rao, Yinyu Nie, Angela Dai |
| 2022 | Patching open-vocabulary models by interpolating weights. Gabriel Ilharco, Mitchell Wortsman, Samir Yitzhak Gadre, Shuran Song, Hannaneh Hajishirzi, Simon Kornblith, Ali Farhadi, Ludwig Schmidt |
| 2022 | Path Independent Equilibrium Models Can Better Exploit Test-Time Computation. Cem Anil, Ashwini Pokle, Kaiqu Liang, Johannes Treutlein, Yuhuai Wu, Shaojie Bai, J. Zico Kolter, Roger B. Grosse |
| 2022 | Pay attention to your loss : understanding misconceptions about Lipschitz neural networks. Louis Béthune, Thibaut Boissin, Mathieu Serrurier, Franck Mamalet, Corentin Friedrich, Alberto González-Sanz |
| 2022 | PeRFception: Perception using Radiance Fields. Yoonwoo Jeong, Seungjoo Shin, Junha Lee, Christopher B. Choy, Anima Anandkumar, Minsu Cho, Jaesik Park |
| 2022 | Peer Prediction for Learning Agents. Shi Feng, Fang-Yi Yu, Yiling Chen |
| 2022 | Perceptual Attacks of No-Reference Image Quality Models with Human-in-the-Loop. Weixia Zhang, Dingquan Li, Xiongkuo Min, Guangtao Zhai, Guodong Guo, Xiaokang Yang, Kede Ma |
| 2022 | Perfect Sampling from Pairwise Comparisons. Dimitris Fotakis, Alkis Kalavasis, Christos Tzamos |
| 2022 | PerfectDou: Dominating DouDizhu with Perfect Information Distillation. Guan Yang, Minghuan Liu, Weijun Hong, Weinan Zhang, Fei Fang, Guangjun Zeng, Yue Lin |
| 2022 | Performative Power. Moritz Hardt, Meena Jagadeesan, Celestine Mendler-Dünner |
| 2022 | Periodic Graph Transformers for Crystal Material Property Prediction. Keqiang Yan, Yi Liu, Yuchao Lin, Shuiwang Ji |
| 2022 | Peripheral Vision Transformer. Juhong Min, Yucheng Zhao, Chong Luo, Minsu Cho |
| 2022 | Personalized Federated Learning towards Communication Efficiency, Robustness and Fairness. Shiyun Lin, Yuze Han, Xiang Li, Zhihua Zhang |
| 2022 | Personalized Online Federated Learning with Multiple Kernels. Pouya M. Ghari, Yanning Shen |
| 2022 | Perturbation Learning Based Anomaly Detection. Jinyu Cai, Jicong Fan |
| 2022 | Pessimism for Offline Linear Contextual Bandits using $\ell_p$ Confidence Sets. Gene Li, Cong Ma, Nati Srebro |
| 2022 | Phase Transition from Clean Training to Adversarial Training. Yue Xing, Qifan Song, Guang Cheng |
| 2022 | Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks. Rodrigo Veiga, Ludovic Stephan, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová |
| 2022 | Phase transitions in when feedback is useful. Lokesh Boominathan, Xaq Pitkow |
| 2022 | Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding. Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L. Denton, Seyed Kamyar Seyed Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J. Fleet, Mohammad Norouzi |
| 2022 | PhysGNN: A Physics-Driven Graph Neural Network Based Model for Predicting Soft Tissue Deformation in Image-Guided Neurosurgery. Yasmin Salehi, Dennis Giannacopoulos |
| 2022 | Physically-Based Face Rendering for NIR-VIS Face Recognition. Yunqi Miao, Alexandros Lattas, Jiankang Deng, Jungong Han, Stefanos Zafeiriou |
| 2022 | Physics-Embedded Neural Networks: Graph Neural PDE Solvers with Mixed Boundary Conditions. Masanobu Horie, Naoto Mitsume |
| 2022 | Physics-Informed Implicit Representations of Equilibrium Network Flows. Kevin D. Smith, Francesco Seccamonte, Ananthram Swami, Francesco Bullo |
| 2022 | Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky, Percy Liang |
| 2022 | Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Peter Henderson, Mark S. Krass, Lucia Zheng, Neel Guha, Christopher D. Manning, Dan Jurafsky, Daniel E. Ho |
| 2022 | Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation. Viktor Bengs, Eyke Hüllermeier, Willem Waegeman |
| 2022 | Plan To Predict: Learning an Uncertainty-Foreseeing Model For Model-Based Reinforcement Learning. Zifan Wu, Chao Yu, Chen Chen, Jianye Hao, Hankz Hankui Zhuo |
| 2022 | Planning for Sample Efficient Imitation Learning. Zhao-Heng Yin, Weirui Ye, Qifeng Chen, Yang Gao |
| 2022 | Planning to the Information Horizon of BAMDPs via Epistemic State Abstraction. Dilip Arumugam, Satinder Singh |
| 2022 | PlasticityNet: Learning to Simulate Metal, Sand, and Snow for Optimization Time Integration. Xuan Li, Yadi Cao, Minchen Li, Yin Yang, Craig A. Schroeder, Chenfanfu Jiang |
| 2022 | Pluralistic Image Completion with Gaussian Mixture Models. Xiaobo Xia, Wenhao Yang, Jie Ren, Yewen Li, Yibing Zhan, Bo Han, Tongliang Liu |
| 2022 | Point Transformer V2: Grouped Vector Attention and Partition-based Pooling. Xiaoyang Wu, Yixing Lao, Li Jiang, Xihui Liu, Hengshuang Zhao |
| 2022 | Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training. Renrui Zhang, Ziyu Guo, Peng Gao, Rongyao Fang, Bin Zhao, Dong Wang, Yu Qiao, Hongsheng Li |
| 2022 | PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies. Guocheng Qian, Yuchen Li, Houwen Peng, Jinjie Mai, Hasan Hammoud, Mohamed Elhoseiny, Bernard Ghanem |
| 2022 | PointTAD: Multi-Label Temporal Action Detection with Learnable Query Points. Jing Tan, Xiaotong Zhao, Xintian Shi, Bin Kang, Limin Wang |
| 2022 | Poisson Flow Generative Models. Yilun Xu, Ziming Liu, Max Tegmark, Tommi S. Jaakkola |
| 2022 | PolarMix: A General Data Augmentation Technique for LiDAR Point Clouds. Aoran Xiao, Jiaxing Huang, Dayan Guan, Kaiwen Cui, Shijian Lu, Ling Shao |
| 2022 | Policy Gradient With Serial Markov Chain Reasoning. Edoardo Cetin, Oya Çeliktutan |
| 2022 | Policy Optimization for Markov Games: Unified Framework and Faster Convergence. Runyu Zhang, Qinghua Liu, Huan Wang, Caiming Xiong, Na Li, Yu Bai |
| 2022 | Policy Optimization with Advantage Regularization for Long-Term Fairness in Decision Systems. Eric Yang Yu, Zhizhen Qin, Min Kyung Lee, Sicun Gao |
| 2022 | Policy Optimization with Linear Temporal Logic Constraints. Cameron Voloshin, Hoang Minh Le, Swarat Chaudhuri, Yisong Yue |
| 2022 | Polyhistor: Parameter-Efficient Multi-Task Adaptation for Dense Vision Tasks. Yen-Cheng Liu, Chih-Yao Ma, Junjiao Tian, Zijian He, Zsolt Kira |
| 2022 | Polynomial Neural Fields for Subband Decomposition and Manipulation. Guandao Yang, Sagie Benaim, Varun Jampani, Kyle Genova, Jonathan T. Barron, Thomas A. Funkhouser, Bharath Hariharan, Serge J. Belongie |
| 2022 | Polynomial time guarantees for the Burer-Monteiro method. Diego Cifuentes, Ankur Moitra |
| 2022 | Polynomial-Time Optimal Equilibria with a Mediator in Extensive-Form Games. Brian Hu Zhang, Tuomas Sandholm |
| 2022 | PopArt: Efficient Sparse Regression and Experimental Design for Optimal Sparse Linear Bandits. Kyoungseok Jang, Chicheng Zhang, Kwang-Sung Jun |
| 2022 | Positive-Unlabeled Learning using Random Forests via Recursive Greedy Risk Minimization. Jonathan Wilton, Abigail M. Y. Koay, Ryan K. L. Ko, Miao Xu, Nan Ye |
| 2022 | Positively Weighted Kernel Quadrature via Subsampling. Satoshi Hayakawa, Harald Oberhauser, Terry J. Lyons |
| 2022 | Post-hoc estimators for learning to defer to an expert. Harikrishna Narasimhan, Wittawat Jitkrittum, Aditya Krishna Menon, Ankit Singh Rawat, Sanjiv Kumar |
| 2022 | Posted Pricing and Dynamic Prior-independent Mechanisms with Value Maximizers. Yuan Deng, Vahab Mirrokni, Hanrui Zhang |
| 2022 | Posterior Collapse of a Linear Latent Variable Model. Zihao Wang, Liu Ziyin |
| 2022 | Posterior Matching for Arbitrary Conditioning. Ryan R. Strauss, Junier B. Oliva |
| 2022 | Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks. Agustinus Kristiadi, Runa Eschenhagen, Philipp Hennig |
| 2022 | Posterior and Computational Uncertainty in Gaussian Processes. Jonathan Wenger, Geoff Pleiss, Marvin Pförtner, Philipp Hennig, John P. Cunningham |
| 2022 | Power and limitations of single-qubit native quantum neural networks. Zhan Yu, Hongshun Yao, Mujin Li, Xin Wang |
| 2022 | Practical Adversarial Attacks on Spatiotemporal Traffic Forecasting Models. Fan Liu, Hao Liu, Wenzhao Jiang |
| 2022 | Practical Adversarial Multivalid Conformal Prediction. Osbert Bastani, Varun Gupta, Christopher Jung, Georgy Noarov, Ramya Ramalingam, Aaron Roth |
| 2022 | Pragmatically Learning from Pedagogical Demonstrations in Multi-Goal Environments. Hugo Caselles-Dupré, Olivier Sigaud, Mohamed Chetouani |
| 2022 | Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors. Ravid Shwartz-Ziv, Micah Goldblum, Hossein Souri, Sanyam Kapoor, Chen Zhu, Yann LeCun, Andrew Gordon Wilson |
| 2022 | Pre-Trained Image Encoder for Generalizable Visual Reinforcement Learning. Zhecheng Yuan, Zhengrong Xue, Bo Yuan, Xueqian Wang, Yi Wu, Yang Gao, Huazhe Xu |
| 2022 | Pre-Trained Language Models for Interactive Decision-Making. Shuang Li, Xavier Puig, Chris Paxton, Yilun Du, Clinton Wang, Linxi Fan, Tao Chen, De-An Huang, Ekin Akyürek, Anima Anandkumar, Jacob Andreas, Igor Mordatch, Antonio Torralba, Yuke Zhu |
| 2022 | Pre-Trained Model Reusability Evaluation for Small-Data Transfer Learning. Yao-Xiang Ding, Xi-Zhu Wu, Kun Zhou, Zhi-Hua Zhou |
| 2022 | Pre-activation Distributions Expose Backdoor Neurons. Runkai Zheng, Rongjun Tang, Jianze Li, Li Liu |
| 2022 | Pre-trained Adversarial Perturbations. Yuanhao Ban, Yinpeng Dong |
| 2022 | Precise Learning Curves and Higher-Order Scalings for Dot-product Kernel Regression. Lechao Xiao, Hong Hu, Theodor Misiakiewicz, Yue Lu, Jeffrey Pennington |
| 2022 | Precise Regret Bounds for Log-loss via a Truncated Bayesian Algorithm. Changlong Wu, Mohsen Heidari, Ananth Grama, Wojciech Szpankowski |
| 2022 | Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution. Leon Hetzel, Simon Böhm, Niki Kilbertus, Stephan Günnemann, Mohammad Lotfollahi, Fabian J. Theis |
| 2022 | Predicting Label Distribution from Multi-label Ranking. Yunan Lu, Xiuyi Jia |
| 2022 | Predictive Coding beyond Gaussian Distributions. Luca Pinchetti, Tommaso Salvatori, Yordan Yordanov, Beren Millidge, Yuhang Song, Thomas Lukasiewicz |
| 2022 | Predictive Querying for Autoregressive Neural Sequence Models. Alex Boyd, Samuel Showalter, Stephan Mandt, Padhraic Smyth |
| 2022 | Preservation of the Global Knowledge by Not-True Distillation in Federated Learning. Gihun Lee, Minchan Jeong, Yongjin Shin, Sangmin Bae, Se-Young Yun |
| 2022 | Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation. Kristian Georgiev, Samuel B. Hopkins |
| 2022 | Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss. Jason M. Altschuler, Kunal Talwar |
| 2022 | Private Estimation with Public Data. Alex Bie, Gautam Kamath, Vikrant Singhal |
| 2022 | Private Graph All-Pairwise-Shortest-Path Distance Release with Improved Error Rate. Chenglin Fan, Ping Li, Xiaoyun Li |
| 2022 | Private Isotonic Regression. Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi |
| 2022 | Private Multiparty Perception for Navigation. Hui Lu, Mia Chiquier, Carl Vondrick |
| 2022 | Private Set Generation with Discriminative Information. Dingfan Chen, Raouf Kerkouche, Mario Fritz |
| 2022 | Private Synthetic Data for Multitask Learning and Marginal Queries. Giuseppe Vietri, Cédric Archambeau, Sergül Aydöre, William Brown, Michael Kearns, Aaron Roth, Amaresh Ankit Siva, Shuai Tang, Zhiwei Steven Wu |
| 2022 | Private and Communication-Efficient Algorithms for Entropy Estimation. Gecia Bravo Hermsdorff, Róbert Busa-Fekete, Mohammad Ghavamzadeh, Andrés Muñoz Medina, Umar Syed |
| 2022 | Probabilistic Missing Value Imputation for Mixed Categorical and Ordered Data. Yuxuan Zhao, Alex Townsend, Madeleine Udell |
| 2022 | Probabilistic Transformer: Modelling Ambiguities and Distributions for RNA Folding and Molecule Design. Jörg K. H. Franke, Frederic Runge, Frank Hutter |
| 2022 | Probable Domain Generalization via Quantile Risk Minimization. Cian Eastwood, Alexander Robey, Shashank Singh, Julius von Kügelgen, Hamed Hassani, George J. Pappas, Bernhard Schölkopf |
| 2022 | Probing Classifiers are Unreliable for Concept Removal and Detection. Abhinav Kumar, Chenhao Tan, Amit Sharma |
| 2022 | Procedural Image Programs for Representation Learning. Manel Baradad, Chun-Fu Richard Chen, Jonas Wulff, Tongzhou Wang, Rogério Feris, Antonio Torralba, Phillip Isola |
| 2022 | Product Ranking for Revenue Maximization with Multiple Purchases. Renzhe Xu, Xingxuan Zhang, Bo Li, Yafeng Zhang, Xiaolong Chen, Peng Cui |
| 2022 | Promising or Elusive? Unsupervised Object Segmentation from Real-world Single Images. Yafei Yang, Bo Yang |
| 2022 | Prompt Certified Machine Unlearning with Randomized Gradient Smoothing and Quantization. Zijie Zhang, Yang Zhou, Xin Zhao, Tianshi Che, Lingjuan Lyu |
| 2022 | Proppo: a Message Passing Framework for Customizable and Composable Learning Algorithms. Paavo Parmas, Takuma Seno |
| 2022 | ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model. Srishti Gautam, Ahcène Boubekki, Stine Hansen, Suaiba Amina Salahuddin, Robert Jenssen, Marina M.-C. Höhne, Michael Kampffmeyer |
| 2022 | ProtoX: Explaining a Reinforcement Learning Agent via Prototyping. Ronilo J. Ragodos, Tong Wang, Qihang Lin, Xun Zhou |
| 2022 | Prototypical VoteNet for Few-Shot 3D Point Cloud Object Detection. Shizhen Zhao, Xiaojuan Qi |
| 2022 | Provable Benefit of Multitask Representation Learning in Reinforcement Learning. Yuan Cheng, Songtao Feng, Jing Yang, Hong Zhang, Yingbin Liang |
| 2022 | Provable Defense against Backdoor Policies in Reinforcement Learning. Shubham Kumar Bharti, Xuezhou Zhang, Adish Singla, Jerry Zhu |
| 2022 | Provable General Function Class Representation Learning in Multitask Bandits and MDP. Rui Lu, Andrew Zhao, Simon S. Du, Gao Huang |
| 2022 | Provable Generalization of Overparameterized Meta-learning Trained with SGD. Yu Huang, Yingbin Liang, Longbo Huang |
| 2022 | Provable Subspace Identification Under Post-Nonlinear Mixtures. Qi Lyu, Xiao Fu |
| 2022 | Provably Adversarially Robust Detection of Out-of-Distribution Data (Almost) for Free. Alexander Meinke, Julian Bitterwolf, Matthias Hein |
| 2022 | Provably Efficient Model-Free Constrained RL with Linear Function Approximation. Arnob Ghosh, Xingyu Zhou, Ness B. Shroff |
| 2022 | Provably Efficient Offline Multi-agent Reinforcement Learning via Strategy-wise Bonus. Qiwen Cui, Simon S. Du |
| 2022 | Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems. Masatoshi Uehara, Ayush Sekhari, Jason D. Lee, Nathan Kallus, Wen Sun |
| 2022 | Provably Feedback-Efficient Reinforcement Learning via Active Reward Learning. Dingwen Kong, Lin Yang |
| 2022 | Provably expressive temporal graph networks. Amauri H. Souza, Diego Mesquita, Samuel Kaski, Vikas Garg |
| 2022 | Provably sample-efficient RL with side information about latent dynamics. Yao Liu, Dipendra Misra, Miro Dudík, Robert E. Schapire |
| 2022 | Provably tuning the ElasticNet across instances. Maria-Florina Balcan, Misha Khodak, Dravyansh Sharma, Ameet Talwalkar |
| 2022 | Proximal Learning With Opponent-Learning Awareness. Stephen Zhao, Chris Lu, Roger B. Grosse, Jakob N. Foerster |
| 2022 | Proximal Point Imitation Learning. Luca Viano, Angeliki Kamoutsi, Gergely Neu, Igor Krawczuk, Volkan Cevher |
| 2022 | Prune and distill: similar reformatting of image information along rat visual cortex and deep neural networks. Paolo Muratore, Sina Tafazoli, Eugenio Piasini, Alessandro Laio, Davide Zoccolan |
| 2022 | Pruning Neural Networks via Coresets and Convex Geometry: Towards No Assumptions. Murad Tukan, Loay Mualem, Alaa Maalouf |
| 2022 | Pruning has a disparate impact on model accuracy. Cuong Tran, Ferdinando Fioretto, Jung-Eun Kim, Rakshit Naidu |
| 2022 | Pruning's Effect on Generalization Through the Lens of Training and Regularization. Tian Jin, Michael Carbin, Daniel M. Roy, Jonathan Frankle, Gintare Karolina Dziugaite |
| 2022 | Pseudo-Riemannian Graph Convolutional Networks. Bo Xiong, Shichao Zhu, Nico Potyka, Shirui Pan, Chuan Zhou, Steffen Staab |
| 2022 | Public Wisdom Matters! Discourse-Aware Hyperbolic Fourier Co-Attention for Social Text Classification. Karish Grover, S. M. Phaneendra Angara, Md. Shad Akhtar, Tanmoy Chakraborty |
| 2022 | PulseImpute: A Novel Benchmark Task for Pulsative Physiological Signal Imputation. Maxwell A. Xu, Alexander Moreno, Supriya Nagesh, Varol Burak Aydemir, David W. Wetter, Santosh Kumar, James M. Rehg |
| 2022 | Pure Transformers are Powerful Graph Learners. Jinwoo Kim, Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong |
| 2022 | Pushing the limits of fairness impossibility: Who's the fairest of them all? Brian Hsu, Rahul Mazumder, Preetam Nandy, Kinjal Basu |
| 2022 | Pyramid Attention For Source Code Summarization. Lei Chai, Ming Li |
| 2022 | PyramidCLIP: Hierarchical Feature Alignment for Vision-language Model Pretraining. Yuting Gao, Jinfeng Liu, Zihan Xu, Jun Zhang, Ke Li, Rongrong Ji, Chunhua Shen |
| 2022 | Pythae: Unifying Generative Autoencoders in Python - A Benchmarking Use Case. Clément Chadebec, Louis J. Vincent, Stéphanie Allassonnière |
| 2022 | Q-ViT: Accurate and Fully Quantized Low-bit Vision Transformer. Yanjing Li, Sheng Xu, Baochang Zhang, Xianbin Cao, Peng Gao, Guodong Guo |
| 2022 | QC-StyleGAN - Quality Controllable Image Generation and Manipulation. Dat Viet Thanh Nguyen, Phong Tran The, Tan M. Dinh, Cuong Pham, Anh Tran |
| 2022 | QUARK: Controllable Text Generation with Reinforced Unlearning. Ximing Lu, Sean Welleck, Jack Hessel, Liwei Jiang, Lianhui Qin, Peter West, Prithviraj Ammanabrolu, Yejin Choi |
| 2022 | Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP. Thao Nguyen, Gabriel Ilharco, Mitchell Wortsman, Sewoong Oh, Ludwig Schmidt |
| 2022 | Quantifying Statistical Significance of Neural Network-based Image Segmentation by Selective Inference. Vo Nguyen Le Duy, Shogo Iwazaki, Ichiro Takeuchi |
| 2022 | Quantile Constrained Reinforcement Learning: A Reinforcement Learning Framework Constraining Outage Probability. Whiyoung Jung, Myungsik Cho, Jongeui Park, Youngchul Sung |
| 2022 | Quantized Training of Gradient Boosting Decision Trees. Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu |
| 2022 | Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants. Andrew M. Childs, Tongyang Li, Jin-Peng Liu, Chunhao Wang, Ruizhe Zhang |
| 2022 | Quantum Speedups of Optimizing Approximately Convex Functions with Applications to Logarithmic Regret Stochastic Convex Bandits. Tongyang Li, Ruizhe Zhang |
| 2022 | Quasi-Newton Methods for Saddle Point Problems. Chengchang Liu, Luo Luo |
| 2022 | QueryPose: Sparse Multi-Person Pose Regression via Spatial-Aware Part-Level Query. Yabo Xiao, Kai Su, Xiaojuan Wang, Dongdong Yu, Lei Jin, Mingshu He, Zehuan Yuan |
| 2022 | Queue Up Your Regrets: Achieving the Dynamic Capacity Region of Multiplayer Bandits. Ilai Bistritz, Nicholas Bambos |
| 2022 | Quo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking? Patrick Dendorfer, Vladimir Yugay, Aljosa Osep, Laura Leal-Taixé |
| 2022 | RAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement Learning. Marc Rigter, Bruno Lacerda, Nick Hawes |
| 2022 | REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question Answering. Yuanze Lin, Yujia Xie, Dongdong Chen, Yichong Xu, Chenguang Zhu, Lu Yuan |
| 2022 | RISE: Robust Individualized Decision Learning with Sensitive Variables. Xiaoqing Tan, Zhengling Qi, Christopher W. Seymour, Lu Tang |
| 2022 | RKHS-SHAP: Shapley Values for Kernel Methods. Siu Lun Chau, Robert Hu, Javier González, Dino Sejdinovic |
| 2022 | RLIP: Relational Language-Image Pre-training for Human-Object Interaction Detection. Hangjie Yuan, Jianwen Jiang, Samuel Albanie, Tao Feng, Ziyuan Huang, Dong Ni, Mingqian Tang |
| 2022 | RNNs of RNNs: Recursive Construction of Stable Assemblies of Recurrent Neural Networks. Leo Kozachkov, Michaela Ennis, Jean-Jacques E. Slotine |
| 2022 | RORL: Robust Offline Reinforcement Learning via Conservative Smoothing. Rui Yang, Chenjia Bai, Xiaoteng Ma, Zhaoran Wang, Chongjie Zhang, Lei Han |
| 2022 | RSA: Reducing Semantic Shift from Aggressive Augmentations for Self-supervised Learning. Yingbin Bai, Erkun Yang, Zhaoqing Wang, Yuxuan Du, Bo Han, Cheng Deng, Dadong Wang, Tongliang Liu |
| 2022 | RTFormer: Efficient Design for Real-Time Semantic Segmentation with Transformer. Jian Wang, Chenhui Gou, Qiman Wu, Haocheng Feng, Junyu Han, Errui Ding, Jingdong Wang |
| 2022 | RainNet: A Large-Scale Imagery Dataset and Benchmark for Spatial Precipitation Downscaling. Xuanhong Chen, Kairui Feng, Naiyuan Liu, Bingbing Ni, Yifan Lu, Zhengyan Tong, Ziang Liu |
| 2022 | Random Normalization Aggregation for Adversarial Defense. Minjing Dong, Xinghao Chen, Yunhe Wang, Chang Xu |
| 2022 | Random Rank: The One and Only Strategyproof and Proportionally Fair Randomized Facility Location Mechanism. Haris Aziz, Alexander Lam, Mashbat Suzuki, Toby Walsh |
| 2022 | Random Sharpness-Aware Minimization. Yong Liu, Siqi Mai, Minhao Cheng, Xiangning Chen, Cho-Jui Hsieh, Yang You |
| 2022 | Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets. Ruisi Cai, Zhenyu Zhang, Tianlong Chen, Xiaohan Chen, Zhangyang Wang |
| 2022 | Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks. Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, Stephan Günnemann |
| 2022 | Randomized Sketches for Clustering: Fast and Optimal Kernel $k$-Means. Rong Yin, Yong Liu, Weiping Wang, Dan Meng |
| 2022 | Rank Diminishing in Deep Neural Networks. Ruili Feng, Kecheng Zheng, Yukun Huang, Deli Zhao, Michael I. Jordan, Zheng-Jun Zha |
| 2022 | RankFeat: Rank-1 Feature Removal for Out-of-distribution Detection. Yue Song, Nicu Sebe, Wei Wang |
| 2022 | Rapid Model Architecture Adaption for Meta-Learning. Yiren Zhao, Xitong Gao, Ilia Shumailov, Nicolò Fusi, Robert Mullins |
| 2022 | Rapidly Mixing Multiple-try Metropolis Algorithms for Model Selection Problems. Hyunwoong Chang, Changwoo J. Lee, Zhao Tang Luo, Huiyan Sang, Quan Zhou |
| 2022 | Rare Gems: Finding Lottery Tickets at Initialization. Kartik Sreenivasan, Jy-yong Sohn, Liu Yang, Matthew Grinde, Alliot Nagle, Hongyi Wang, Eric P. Xing, Kangwook Lee, Dimitris S. Papailiopoulos |
| 2022 | Rashomon Capacity: A Metric for Predictive Multiplicity in Classification. Hsiang Hsu, Flávio P. Calmon |
| 2022 | Rate-Distortion Theoretic Bounds on Generalization Error for Distributed Learning. Milad Sefidgaran, Romain Chor, Abdellatif Zaidi |
| 2022 | Rate-Optimal Online Convex Optimization in Adaptive Linear Control. Asaf B. Cassel, Alon Peled-Cohen, Tomer Koren |
| 2022 | Re-Analyze Gauss: Bounds for Private Matrix Approximation via Dyson Brownian Motion. Oren Mangoubi, Nisheeth K. Vishnoi |
| 2022 | ReCo: Retrieve and Co-segment for Zero-shot Transfer. Gyungin Shin, Weidi Xie, Samuel Albanie |
| 2022 | ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective. Yihong Chen, Pushkar Mishra, Luca Franceschi, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel |
| 2022 | Real-Valued Backpropagation is Unsuitable for Complex-Valued Neural Networks. Zhi-Hao Tan, Yi Xie, Yuan Jiang, Zhi-Hua Zhou |
| 2022 | Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm. Aidan Good, Jiaqi Lin, Xin Yu, Hannah Sieg, Mikey Ferguson, Shandian Zhe, Jerzy Wieczorek, Thiago Serra |
| 2022 | Receding Horizon Inverse Reinforcement Learning. Yiqing Xu, Wei Gao, David Hsu |
| 2022 | Recipe for a General, Powerful, Scalable Graph Transformer. Ladislav Rampásek, Michael Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini |
| 2022 | Recommender Forest for Efficient Retrieval. Chao Feng, Wuchao Li, Defu Lian, Zheng Liu, Enhong Chen |
| 2022 | Reconstructing Training Data From Trained Neural Networks. Niv Haim, Gal Vardi, Gilad Yehudai, Ohad Shamir, Michal Irani |
| 2022 | Reconstruction on Trees and Low-Degree Polynomials. Frederic Koehler, Elchanan Mossel |
| 2022 | Recovering Private Text in Federated Learning of Language Models. Samyak Gupta, Yangsibo Huang, Zexuan Zhong, Tianyu Gao, Kai Li, Danqi Chen |
| 2022 | Recruitment Strategies That Take a Chance. Gregory Kehne, Ariel D. Procaccia, Jingyan Wang |
| 2022 | Recurrent Convolutional Neural Networks Learn Succinct Learning Algorithms. Surbhi Goel, Sham M. Kakade, Adam Kalai, Cyril Zhang |
| 2022 | Recurrent Memory Transformer. Aydar Bulatov, Yuri Kuratov, Mikhail Burtsev |
| 2022 | Recurrent Video Restoration Transformer with Guided Deformable Attention. Jingyun Liang, Yuchen Fan, Xiaoyu Xiang, Rakesh Ranjan, Eddy Ilg, Simon Green, Jiezhang Cao, Kai Zhang, Radu Timofte, Luc Van Gool |
| 2022 | Recursive Reasoning in Minimax Games: A Level $k$ Gradient Play Method. Zichu Liu, Lacra Pavel |
| 2022 | Recursive Reinforcement Learning. Ernst Moritz Hahn, Mateo Perez, Sven Schewe, Fabio Somenzi, Ashutosh Trivedi, Dominik Wojtczak |
| 2022 | RecursiveMix: Mixed Learning with History. Lingfeng Yang, Xiang Li, Borui Zhao, Renjie Song, Jian Yang |
| 2022 | Redeeming intrinsic rewards via constrained optimization. Eric Chen, Zhang-Wei Hong, Joni Pajarinen, Pulkit Agrawal |
| 2022 | Redistribution of Weights and Activations for AdderNet Quantization. Ying Nie, Kai Han, Haikang Diao, Chuanjian Liu, Enhua Wu, Yunhe Wang |
| 2022 | Reduced Representation of Deformation Fields for Effective Non-rigid Shape Matching. Ramana Sundararaman, Riccardo Marin, Emanuele Rodolà, Maks Ovsjanikov |
| 2022 | Reduction Algorithms for Persistence Diagrams of Networks: CoralTDA and PrunIT. Cuneyt Gurcan Akcora, Murat Kantarcioglu, Yulia R. Gel, Baris Coskunuzer |
| 2022 | Redundancy-Free Message Passing for Graph Neural Networks. Rongqin Chen, Shenghui Zhang, Leong Hou U, Ye Li |
| 2022 | Redundant representations help generalization in wide neural networks. Diego Doimo, Aldo Glielmo, Sebastian Goldt, Alessandro Laio |
| 2022 | Refining Low-Resource Unsupervised Translation by Language Disentanglement of Multilingual Translation Model. Xuan-Phi Nguyen, Shafiq R. Joty, Kui Wu, Ai Ti Aw |
| 2022 | Regret Bounds for Information-Directed Reinforcement Learning. Botao Hao, Tor Lattimore |
| 2022 | Regret Bounds for Multilabel Classification in Sparse Label Regimes. Róbert Busa-Fekete, Heejin Choi, Krzysztof Dembczynski, Claudio Gentile, Henry Reeve, Balázs Szörényi |
| 2022 | Regret Bounds for Risk-Sensitive Reinforcement Learning. Osbert Bastani, Yecheng Jason Ma, Estelle Shen, Wanqiao Xu |
| 2022 | Regularized Gradient Descent Ascent for Two-Player Zero-Sum Markov Games. Sihan Zeng, Thinh T. Doan, Justin Romberg |
| 2022 | Regularized Molecular Conformation Fields. Lihao Wang, Yi Zhou, Yiqun Wang, Xiaoqing Zheng, Xuanjing Huang, Hao Zhou |
| 2022 | Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress. Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, Aaron C. Courville, Marc G. Bellemare |
| 2022 | Reinforced Genetic Algorithm for Structure-based Drug Design. Tianfan Fu, Wenhao Gao, Connor W. Coley, Jimeng Sun |
| 2022 | Reinforcement Learning in a Birth and Death Process: Breaking the Dependence on the State Space. Jonatha Anselmi, Bruno Gaujal, Louis-Sébastien Rebuffi |
| 2022 | Reinforcement Learning with Automated Auxiliary Loss Search. Tairan He, Yuge Zhang, Kan Ren, Minghuan Liu, Che Wang, Weinan Zhang, Yuqing Yang, Dongsheng Li |
| 2022 | Reinforcement Learning with Logarithmic Regret and Policy Switches. Grigoris Velegkas, Zhuoran Yang, Amin Karbasi |
| 2022 | Reinforcement Learning with Neural Radiance Fields. Danny Driess, Ingmar Schubert, Pete Florence, Yunzhu Li, Marc Toussaint |
| 2022 | Reinforcement Learning with Non-Exponential Discounting. Matthias Schultheis, Constantin A. Rothkopf, Heinz Koeppl |
| 2022 | Reinforcement Learning with a Terminator. Guy Tennenholtz, Nadav Merlis, Lior Shani, Shie Mannor, Uri Shalit, Gal Chechik, Assaf Hallak, Gal Dalal |
| 2022 | Relation-Constrained Decoding for Text Generation. Xiang Chen, Zhixian Yang, Xiaojun Wan |
| 2022 | Relational Proxies: Emergent Relationships as Fine-Grained Discriminators. Abhra Chaudhuri, Massimiliano Mancini, Zeynep Akata, Anjan Dutta |
| 2022 | Relational Reasoning via Set Transformers: Provable Efficiency and Applications to MARL. Fengzhuo Zhang, Boyi Liu, Kaixin Wang, Vincent Y. F. Tan, Zhuoran Yang, Zhaoran Wang |
| 2022 | Relaxing Equivariance Constraints with Non-stationary Continuous Filters. Tycho F. A. van der Ouderaa, David W. Romero, Mark van der Wilk |
| 2022 | Remember the Past: Distilling Datasets into Addressable Memories for Neural Networks. Zhiwei Deng, Olga Russakovsky |
| 2022 | Renyi Differential Privacy of Propose-Test-Release and Applications to Private and Robust Machine Learning. Jiachen T. Wang, Saeed Mahloujifar, Shouda Wang, Ruoxi Jia, Prateek Mittal |
| 2022 | Repairing Neural Networks by Leaving the Right Past Behind. Ryutaro Tanno, Melanie F. Pradier, Aditya V. Nori, Yingzhen Li |
| 2022 | Representing Spatial Trajectories as Distributions. Dídac Surís, Carl Vondrick |
| 2022 | Reproducibility in Optimization: Theoretical Framework and Limits. Kwangjun Ahn, Prateek Jain, Ziwei Ji, Satyen Kale, Praneeth Netrapalli, Gil I. Shamir |
| 2022 | ResQ: A Residual Q Function-based Approach for Multi-Agent Reinforcement Learning Value Factorization. Siqi Shen, Mengwei Qiu, Jun Liu, Weiquan Liu, Yongquan Fu, Xinwang Liu, Cheng Wang |
| 2022 | ResT V2: Simpler, Faster and Stronger. Qinglong Zhang, Yu-Bin Yang |
| 2022 | Residual Multiplicative Filter Networks for Multiscale Reconstruction. Shayan Shekarforoush, David B. Lindell, David J. Fleet, Marcus A. Brubaker |
| 2022 | Resolving the data ambiguity for periodic crystals. Daniel Widdowson, Vitaliy Kurlin |
| 2022 | Resource-Adaptive Federated Learning with All-In-One Neural Composition. Yiqun Mei, Pengfei Guo, Mo Zhou, Vishal Patel |
| 2022 | Respecting Transfer Gap in Knowledge Distillation. Yulei Niu, Long Chen, Chang Zhou, Hanwang Zhang |
| 2022 | Retaining Knowledge for Learning with Dynamic Definition. Zichang Liu, Benjamin Coleman, Tianyi Zhang, Anshumali Shrivastava |
| 2022 | Rethinking Alignment in Video Super-Resolution Transformers. Shuwei Shi, Jinjin Gu, Liangbin Xie, Xintao Wang, Yujiu Yang, Chao Dong |
| 2022 | Rethinking Generalization in Few-Shot Classification. Markus Hiller, Rongkai Ma, Mehrtash Harandi, Tom Drummond |
| 2022 | Rethinking Image Restoration for Object Detection. Shangquan Sun, Wenqi Ren, Tao Wang, Xiaochun Cao |
| 2022 | Rethinking Individual Global Max in Cooperative Multi-Agent Reinforcement Learning. Yitian Hong, Yaochu Jin, Yang Tang |
| 2022 | Rethinking Knowledge Graph Evaluation Under the Open-World Assumption. Haotong Yang, Zhouchen Lin, Muhan Zhang |
| 2022 | Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective. Bohang Zhang, Du Jiang, Di He, Liwei Wang |
| 2022 | Rethinking Resolution in the Context of Efficient Video Recognition. Chuofan Ma, Qiushan Guo, Yi Jiang, Ping Luo, Zehuan Yuan, Xiaojuan Qi |
| 2022 | Rethinking Value Function Learning for Generalization in Reinforcement Learning. Seungyong Moon, Junyeong Lee, Hyun Oh Song |
| 2022 | Rethinking Variational Inference for Probabilistic Programs with Stochastic Support. Tim Reichelt, Luke Ong, Thomas Rainforth |
| 2022 | Rethinking and Improving Robustness of Convolutional Neural Networks: a Shapley Value-based Approach in Frequency Domain. Yiting Chen, Qibing Ren, Junchi Yan |
| 2022 | Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination. Yizhen Zheng, Shirui Pan, Vincent C. S. Lee, Yu Zheng, Philip S. Yu |
| 2022 | Rethinking the Reverse-engineering of Trojan Triggers. Zhenting Wang, Kai Mei, Hailun Ding, Juan Zhai, Shiqing Ma |
| 2022 | Rethinking the compositionality of point clouds through regularization in the hyperbolic space. Antonio Montanaro, Diego Valsesia, Enrico Magli |
| 2022 | Retrieval-Augmented Diffusion Models. Andreas Blattmann, Robin Rombach, Kaan Oktay, Jonas Müller, Björn Ommer |
| 2022 | Retrieve, Reason, and Refine: Generating Accurate and Faithful Patient Instructions. Fenglin Liu, Bang Yang, Chenyu You, Xian Wu, Shen Ge, Zhangdaihong Liu, Xu Sun, Yang Yang, David A. Clifton |
| 2022 | Retrospective Adversarial Replay for Continual Learning. Lilly Kumari, Shengjie Wang, Tianyi Zhou, Jeff A. Bilmes |
| 2022 | Revisit last-iterate convergence of mSGD under milder requirement on step size. Ruinan Jin, Xingkang He, Lang Chen, Difei Cheng, Vijay Gupta |
| 2022 | Revisiting Active Sets for Gaussian Process Decoders. Pablo Moreno-Muñoz, Cilie W. Feldager, Søren Hauberg |
| 2022 | Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum. Nian Liu, Xiao Wang, Deyu Bo, Chuan Shi, Jian Pei |
| 2022 | Revisiting Heterophily For Graph Neural Networks. Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Mingde Zhao, Shuyuan Zhang, Xiao-Wen Chang, Doina Precup |
| 2022 | Revisiting Injective Attacks on Recommender Systems. Haoyang Li, Shimin Di, Lei Chen |
| 2022 | Revisiting Neural Scaling Laws in Language and Vision. Ibrahim M. Alabdulmohsin, Behnam Neyshabur, Xiaohua Zhai |
| 2022 | Revisiting Non-Parametric Matching Cost Volumes for Robust and Generalizable Stereo Matching. Kelvin Cheng, Tianfu Wu, Christopher G. Healey |
| 2022 | Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization. Kun Yuan, Xinmeng Huang, Yiming Chen, Xiaohan Zhang, Yingya Zhang, Pan Pan |
| 2022 | Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering. Yongyi Su, Xun Xu, Kui Jia |
| 2022 | Revisiting Sliced Wasserstein on Images: From Vectorization to Convolution. Khai Nguyen, Nhat Ho |
| 2022 | Revisiting Sparse Convolutional Model for Visual Recognition. Xili Dai, Mingyang Li, Pengyuan Zhai, Shengbang Tong, Xingjian Gao, Shao-Lun Huang, Zhihui Zhu, Chong You, Yi Ma |
| 2022 | Riemannian Diffusion Models. Chin-Wei Huang, Milad Aghajohari, Joey Bose, Prakash Panangaden, Aaron C. Courville |
| 2022 | Riemannian Neural SDE: Learning Stochastic Representations on Manifolds. Sung Woo Park, Hyomin Kim, Kyungjae Lee, Junseok Kwon |
| 2022 | Riemannian Score-Based Generative Modelling. Valentin De Bortoli, Emile Mathieu, Michael J. Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet |
| 2022 | Risk Bounds of Multi-Pass SGD for Least Squares in the Interpolation Regime. Difan Zou, Jingfeng Wu, Vladimir Braverman, Quanquan Gu, Sham M. Kakade |
| 2022 | Risk-Driven Design of Perception Systems. Anthony Corso, Sydney M. Katz, Craig Innes, Xin Du, Subramanian Ramamoorthy, Mykel J. Kochenderfer |
| 2022 | Roadblocks for Temporarily Disabling Shortcuts and Learning New Knowledge. Hongjing Niu, Hanting Li, Feng Zhao, Bin Li |
| 2022 | Robust $\phi$-Divergence MDPs. Chin Pang Ho, Marek Petrik, Wolfram Wiesemann |
| 2022 | Robust Anytime Learning of Markov Decision Processes. Marnix Suilen, Thiago D. Simão, David Parker, Nils Jansen |
| 2022 | Robust Bayesian Regression via Hard Thresholding. Zheyi Fan, Zhaohui Li, Qingpei Hu |
| 2022 | Robust Binary Models by Pruning Randomly-initialized Networks. Chen Liu, Ziqi Zhao, Sabine Süsstrunk, Mathieu Salzmann |
| 2022 | Robust Calibration with Multi-domain Temperature Scaling. Yaodong Yu, Stephen Bates, Yi Ma, Michael I. Jordan |
| 2022 | Robust Feature-Level Adversaries are Interpretability Tools. Stephen Casper, Max Nadeau, Dylan Hadfield-Menell, Gabriel Kreiman |
| 2022 | Robust Generalized Method of Moments: A Finite Sample Viewpoint. Dhruv Rohatgi, Vasilis Syrgkanis |
| 2022 | Robust Graph Structure Learning via Multiple Statistical Tests. Yaohua Wang, Fangyi Zhang, Ming Lin, Senzhang Wang, Xiuyu Sun, Rong Jin |
| 2022 | Robust Imitation of a Few Demonstrations with a Backwards Model. Jung Yeon Park, Lawson L. S. Wong |
| 2022 | Robust Imitation via Mirror Descent Inverse Reinforcement Learning. Dong-Sig Han, Hyunseo Kim, Hyundo Lee, Je-Hwan Ryu, Byoung-Tak Zhang |
| 2022 | Robust Learning against Relational Adversaries. Yizhen Wang, Mohannad Alhanahnah, Xiaozhu Meng, Ke Wang, Mihai Christodorescu, Somesh Jha |
| 2022 | Robust Model Selection and Nearly-Proper Learning for GMMs. Allen Liu, Jerry Li, Ankur Moitra |
| 2022 | Robust Models are less Over-Confident. Julia Grabinski, Paul Gavrikov, Janis Keuper, Margret Keuper |
| 2022 | Robust Neural Posterior Estimation and Statistical Model Criticism. Daniel Ward, Patrick Cannon, Mark Beaumont, Matteo Fasiolo, Sebastian M. Schmon |
| 2022 | Robust On-Policy Sampling for Data-Efficient Policy Evaluation in Reinforcement Learning. Rujie Zhong, Duohan Zhang, Lukas Schäfer, Stefano V. Albrecht, Josiah Hanna |
| 2022 | Robust Reinforcement Learning using Offline Data. Kishan Panaganti, Zaiyan Xu, Dileep Kalathil, Mohammad Ghavamzadeh |
| 2022 | Robust Rent Division. Dominik Peters, Ariel D. Procaccia, David Zhu |
| 2022 | Robust Semi-Supervised Learning when Not All Classes have Labels. Lan-Zhe Guo, Yi-Ge Zhang, Zhi-Fan Wu, Jie-Jing Shao, Yufeng Li |
| 2022 | Robust Streaming PCA. Daniel Bienstock, Minchan Jeong, Apurv Shukla, Se-Young Yun |
| 2022 | Robust Testing in High-Dimensional Sparse Models. Anand Jerry George, Clément L. Canonne |
| 2022 | Robustness Analysis of Video-Language Models Against Visual and Language Perturbations. Madeline Schiappa, Shruti Vyas, Hamid Palangi, Yogesh S. Rawat, Vibhav Vineet |
| 2022 | Robustness Disparities in Face Detection. Samuel Dooley, George Z. Wei, Tom Goldstein, John Dickerson |
| 2022 | Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization). Zhenyu Zhu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher |
| 2022 | Robustness to Label Noise Depends on the Shape of the Noise Distribution. Diane Oyen, Michal Kucer, Nicolas W. Hengartner, Har Simrat Singh |
| 2022 | Robustness to Unbounded Smoothness of Generalized SignSGD. Michael Crawshaw, Mingrui Liu, Francesco Orabona, Wei Zhang, Zhenxun Zhuang |
| 2022 | Root Cause Analysis of Failures in Microservices through Causal Discovery. Azam Ikram, Sarthak Chakraborty, Subrata Mitra, Shiv Kumar Saini, Saurabh Bagchi, Murat Kocaoglu |
| 2022 | Rotation-Equivariant Conditional Spherical Neural Fields for Learning a Natural Illumination Prior. James A. D. Gardner, Bernhard Egger, William Smith |
| 2022 | RényiCL: Contrastive Representation Learning with Skew Rényi Divergence. Kyungmin Lee, Jinwoo Shin |
| 2022 | S Wenqi Yang, Guanying Chen, Chaofeng Chen, Zhenfang Chen, Kwan-Yee K. Wong |
| 2022 | S-PIFu: Integrating Parametric Human Models with PIFu for Single-view Clothed Human Reconstruction. Kennard Yanting Chan, Guosheng Lin, Haiyu Zhao, Weisi Lin |
| 2022 | S-Prompts Learning with Pre-trained Transformers: An Occam's Razor for Domain Incremental Learning. Yabin Wang, Zhiwu Huang, Xiaopeng Hong |
| 2022 | S2P: State-conditioned Image Synthesis for Data Augmentation in Offline Reinforcement Learning. Daesol Cho, Dongseok Shim, H. Jin Kim |
| 2022 | S3GC: Scalable Self-Supervised Graph Clustering. Devvrit, Aditya Sinha, Inderjit S. Dhillon, Prateek Jain |
| 2022 | S4ND: Modeling Images and Videos as Multidimensional Signals with State Spaces. Eric Nguyen, Karan Goel, Albert Gu, Gordon W. Downs, Preey Shah, Tri Dao, Stephen Baccus, Christopher Ré |
| 2022 | SAGDA: Achieving $\mathcal{O}(\epsilon^{-2})$ Communication Complexity in Federated Min-Max Learning. Haibo Yang, Zhuqing Liu, Xin Zhang, Jia Liu |
| 2022 | SALSA: Attacking Lattice Cryptography with Transformers. Emily Wenger, Mingjie Chen, François Charton, Kristin E. Lauter |
| 2022 | SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections. Mark Boss, Andreas Engelhardt, Abhishek Kar, Yuanzhen Li, Deqing Sun, Jonathan T. Barron, Hendrik P. A. Lensch, Varun Jampani |
| 2022 | SAPA: Similarity-Aware Point Affiliation for Feature Upsampling. Hao Lu, Wenze Liu, Zixuan Ye, Hongtao Fu, Yuliang Liu, Zhiguo Cao |
| 2022 | SAPD+: An Accelerated Stochastic Method for Nonconvex-Concave Minimax Problems. Xuan Zhang, Necdet Serhat Aybat, Mert Gürbüzbalaban |
| 2022 | SAPipe: Staleness-Aware Pipeline for Data Parallel DNN Training. Yangrui Chen, Cong Xie, Meng Ma, Juncheng Gu, Yanghua Peng, Haibin Lin, Chuan Wu, Yibo Zhu |
| 2022 | SAVi++: Towards End-to-End Object-Centric Learning from Real-World Videos. Gamaleldin F. Elsayed, Aravindh Mahendran, Sjoerd van Steenkiste, Klaus Greff, Michael C. Mozer, Thomas Kipf |
| 2022 | SAViT: Structure-Aware Vision Transformer Pruning via Collaborative Optimization. Chuanyang Zheng, Zheyang Li, Kai Zhang, Zhi Yang, Wenming Tan, Jun Xiao, Ye Ren, Shiliang Pu |
| 2022 | SCAMPS: Synthetics for Camera Measurement of Physiological Signals. Daniel McDuff, Miah Wander, Xin Liu, Brian L. Hill, Javier Hernandez, Jonathan Lester, Tadas Baltrusaitis |
| 2022 | SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction. Minhao Liu, Ailing Zeng, Muxi Chen, Zhijian Xu, Qiuxia Lai, Lingna Ma, Qiang Xu |
| 2022 | SCL-WC: Cross-Slide Contrastive Learning for Weakly-Supervised Whole-Slide Image Classification. Xiyue Wang, Jinxi Xiang, Jun Zhang, Sen Yang, Zhongyi Yang, Ming-Hui Wang, Jing Zhang, Wei Yang, Junzhou Huang, Xiao Han |
| 2022 | SCONE: Surface Coverage Optimization in Unknown Environments by Volumetric Integration. Antoine Guédon, Pascal Monasse, Vincent Lepetit |
| 2022 | SGAM: Building a Virtual 3D World through Simultaneous Generation and Mapping. Yuan Shen, Wei-Chiu Ma, Shenlong Wang |
| 2022 | SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning. Jianhong Wang, Yuan Zhang, Yunjie Gu, Tae-Kyun Kim |
| 2022 | SHINE: SubHypergraph Inductive Neural nEtwork. Yuan Luo |
| 2022 | SIREN: Shaping Representations for Detecting Out-of-Distribution Objects. Xuefeng Du, Gabriel Gozum, Yifei Ming, Yixuan Li |
| 2022 | SIXO: Smoothing Inference with Twisted Objectives. Dieterich Lawson, Allan Raventós, Andrew Warrington, Scott W. Linderman |
| 2022 | SInGE: Sparsity via Integrated Gradients Estimation of Neuron Relevance. Edouard Yvinec, Arnaud Dapogny, Matthieu Cord, Kevin Bailly |
| 2022 | SKFlow: Learning Optical Flow with Super Kernels. Shangkun Sun, Yuanqi Chen, Yu Zhu, Guodong Guo, Ge Li |
| 2022 | SMPL: Simulated Industrial Manufacturing and Process Control Learning Environments. Mohan Zhang, Xiaozhou Wang, Benjamin Decardi-Nelson, Song Bo, An Zhang, Jinfeng Liu, Sile Tao, Jiayi Cheng, Xiaohong Liu, Dengdeng Yu, Matthew Poon, Animesh Garg |
| 2022 | SNAKE: Shape-aware Neural 3D Keypoint Field. Chengliang Zhong, Peixing You, Xiaoxue Chen, Hao Zhao, Fuchun Sun, Guyue Zhou, Xiaodong Mu, Chuang Gan, Wenbing Huang |
| 2022 | SNN-RAT: Robustness-enhanced Spiking Neural Network through Regularized Adversarial Training. Jianhao Ding, Tong Bu, Zhaofei Yu, Tiejun Huang, Jian K. Liu |
| 2022 | SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG. Reinmar J. Kobler, Jun-ichiro Hirayama, Qibin Zhao, Motoaki Kawanabe |
| 2022 | SPD: Synergy Pattern Diversifying Oriented Unsupervised Multi-agent Reinforcement Learning. Yuhang Jiang, Jianzhun Shao, Shuncheng He, Hongchang Zhang, Xiangyang Ji |
| 2022 | SPoVT: Semantic-Prototype Variational Transformer for Dense Point Cloud Semantic Completion. Sheng-Yu Huang, Hao-Yu Hsu, Yu-Chiang Frank Wang |
| 2022 | SQ Lower Bounds for Learning Single Neurons with Massart Noise. Ilias Diakonikolas, Daniel Kane, Lisheng Ren, Yuxin Sun |
| 2022 | ST-Adapter: Parameter-Efficient Image-to-Video Transfer Learning. Junting Pan, Ziyi Lin, Xiatian Zhu, Jing Shao, Hongsheng Li |
| 2022 | STNDT: Modeling Neural Population Activity with Spatiotemporal Transformers. Trung Le, Eli Shlizerman |
| 2022 | STaR: Bootstrapping Reasoning With Reasoning. Eric Zelikman, Yuhuai Wu, Jesse Mu, Noah D. Goodman |
| 2022 | Safe Opponent-Exploitation Subgame Refinement. Mingyang Liu, Chengjie Wu, Qihan Liu, Yansen Jing, Jun Yang, Pingzhong Tang, Chongjie Zhang |
| 2022 | SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles. Chejian Xu, Wenhao Ding, Weijie Lyu, Zuxin Liu, Shuai Wang, Yihan He, Hanjiang Hu, Ding Zhao, Bo Li |
| 2022 | Safety Guarantees for Neural Network Dynamic Systems via Stochastic Barrier Functions. Rayan Mazouz, Karan Muvvala, Akash Ratheesh, Luca Laurenti, Morteza Lahijanian |
| 2022 | SageMix: Saliency-Guided Mixup for Point Clouds. Sanghyeok Lee, Minkyu Jeon, Injae Kim, Yunyang Xiong, Hyunwoo J. Kim |
| 2022 | Saliency-Aware Neural Architecture Search. Ramtin Hosseini, Pengtao Xie |
| 2022 | Sample Complexity of Learning Heuristic Functions for Greedy-Best-First and A* Search. Shinsaku Sakaue, Taihei Oki |
| 2022 | Sample Constrained Treatment Effect Estimation. Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao |
| 2022 | Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization. Wenhao Gao, Tianfan Fu, Jimeng Sun, Connor W. Coley |
| 2022 | Sample-Efficient Learning of Correlated Equilibria in Extensive-Form Games. Ziang Song, Song Mei, Yu Bai |
| 2022 | Sample-Efficient Reinforcement Learning of Partially Observable Markov Games. Qinghua Liu, Csaba Szepesvári, Chi Jin |
| 2022 | Sample-Then-Optimize Batch Neural Thompson Sampling. Zhongxiang Dai, Yao Shu, Bryan Kian Hsiang Low, Patrick Jaillet |
| 2022 | Sampling from Log-Concave Distributions with Infinity-Distance Guarantees. Oren Mangoubi, Nisheeth K. Vishnoi |
| 2022 | Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent. Ruqi Zhang, Qiang Liu, Xin T. Tong |
| 2022 | Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space. Yunbum Kook, Yin Tat Lee, Ruoqi Shen, Santosh S. Vempala |
| 2022 | Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization. Aniket Das, Bernhard Schölkopf, Michael Muehlebach |
| 2022 | SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery. Yezhen Cong, Samar Khanna, Chenlin Meng, Patrick Liu, Erik Rozi, Yutong He, Marshall Burke, David B. Lobell, Stefano Ermon |
| 2022 | Scalable Distributional Robustness in a Class of Non-Convex Optimization with Guarantees. Avinandan Bose, Arunesh Sinha, Tien Mai |
| 2022 | Scalable Infomin Learning. Yanzhi Chen, Weihao Sun, Yingzhen Li, Adrian Weller |
| 2022 | Scalable Interpretability via Polynomials. Abhimanyu Dubey, Filip Radenovic, Dhruv Mahajan |
| 2022 | Scalable Multi-agent Covering Option Discovery based on Kronecker Graphs. Jiayu Chen, Jingdi Chen, Tian Lan, Vaneet Aggarwal |
| 2022 | Scalable Neural Video Representations with Learnable Positional Features. Subin Kim, Sihyun Yu, Jaeho Lee, Jinwoo Shin |
| 2022 | Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees. Andrea Tirinzoni, Matteo Papini, Ahmed Touati, Alessandro Lazaric, Matteo Pirotta |
| 2022 | Scalable Sensitivity and Uncertainty Analyses for Causal-Effect Estimates of Continuous-Valued Interventions. Andrew Jesson, Alyson Douglas, Peter Manshausen, Maëlys Solal, Nicolai Meinshausen, Philip Stier, Yarin Gal, Uri Shalit |
| 2022 | Scalable and Efficient Non-adaptive Deterministic Group Testing. Dariusz R. Kowalski, Dominik Pajak |
| 2022 | Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy. Zhiqi Bu, Jialin Mao, Shiyun Xu |
| 2022 | Scalable design of Error-Correcting Output Codes using Discrete Optimization with Graph Coloring. Samarth Gupta, Saurabh Amin |
| 2022 | Scale-invariant Learning by Physics Inversion. Philipp Holl, Vladlen Koltun, Nils Thuerey |
| 2022 | Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning. Dongze Lian, Daquan Zhou, Jiashi Feng, Xinchao Wang |
| 2022 | Scaling Multimodal Pre-Training via Cross-Modality Gradient Harmonization. Junru Wu, Yi Liang, Feng Han, Hassan Akbari, Zhangyang Wang, Cong Yu |
| 2022 | Score-Based Diffusion meets Annealed Importance Sampling. Arnaud Doucet, Will Grathwohl, Alexander G. de G. Matthews, Heiko Strathmann |
| 2022 | Score-Based Generative Models Detect Manifolds. Jakiw Pidstrigach |
| 2022 | Score-based Generative Modeling Secretly Minimizes the Wasserstein Distance. Dohyun Kwon, Ying Fan, Kangwook Lee |
| 2022 | Searching for Better Spatio-temporal Alignment in Few-Shot Action Recognition. Yichao Cao, Xiu Su, Qingfei Tang, Shan You, Xiaobo Lu, Chang Xu |
| 2022 | Second Thoughts are Best: Learning to Re-Align With Human Values from Text Edits. Ruibo Liu, Chenyan Jia, Ge Zhang, Ziyu Zhuang, Tony X. Liu, Soroush Vosoughi |
| 2022 | SecureFedYJ: a safe feature Gaussianization protocol for Federated Learning. Tanguy Marchand, Boris Muzellec, Constance Beguier, Jean Ogier du Terrail, Mathieu Andreux |
| 2022 | Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers. Ran Liu, Mehdi Azabou, Max Dabagia, Jingyun Xiao, Eva L. Dyer |
| 2022 | SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation. Meng-Hao Guo, Cheng-Ze Lu, Qibin Hou, Zhengning Liu, Ming-Ming Cheng, Shi-Min Hu |
| 2022 | SegViT: Semantic Segmentation with Plain Vision Transformers. Bowen Zhang, Zhi Tian, Quan Tang, Xiangxiang Chu, Xiaolin Wei, Chunhua Shen, Yifan Liu |
| 2022 | Segmenting Moving Objects via an Object-Centric Layered Representation. Junyu Xie, Weidi Xie, Andrew Zisserman |
| 2022 | SelecMix: Debiased Learning by Contradicting-pair Sampling. Inwoo Hwang, Sangjun Lee, Yunhyeok Kwak, Seong Joon Oh, Damien Teney, Jin-Hwa Kim, Byoung-Tak Zhang |
| 2022 | Selective compression learning of latent representations for variable-rate image compression. Jooyoung Lee, Seyoon Jeong, Munchurl Kim |
| 2022 | Self-Aware Personalized Federated Learning. Huili Chen, Jie Ding, Eric W. Tramel, Shuang Wu, Anit Kumar Sahu, Salman Avestimehr, Tao Zhang |
| 2022 | Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks. Blake Bordelon, Cengiz Pehlevan |
| 2022 | Self-Explaining Deviations for Coordination. Hengyuan Hu, Samuel Sokota, David J. Wu, Anton Bakhtin, Andrei Lupu, Brandon Cui, Jakob N. Foerster |
| 2022 | Self-Organized Group for Cooperative Multi-agent Reinforcement Learning. Jianzhun Shao, Zhiqiang Lou, Hongchang Zhang, Yuhang Jiang, Shuncheng He, Xiangyang Ji |
| 2022 | Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations. Michael Poli, Winnie Xu, Stefano Massaroli, Chenlin Meng, Kuno Kim, Stefano Ermon |
| 2022 | Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition. Yifan Zhang, Bryan Hooi, Lanqing Hong, Jiashi Feng |
| 2022 | Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency. Xiang Zhang, Ziyuan Zhao, Theodoros Tsiligkaridis, Marinka Zitnik |
| 2022 | Self-Supervised Fair Representation Learning without Demographics. Junyi Chai, Xiaoqian Wang |
| 2022 | Self-Supervised Image Restoration with Blurry and Noisy Pairs. Zhilu Zhang, Rongjian Xu, Ming Liu, Zifei Yan, Wangmeng Zuo |
| 2022 | Self-Supervised Learning Through Efference Copies. Franz Scherr, Qinghai Guo, Timoleon Moraitis |
| 2022 | Self-Supervised Learning of Brain Dynamics from Broad Neuroimaging Data. Armin W. Thomas, Christopher Ré, Russell A. Poldrack |
| 2022 | Self-Supervised Learning via Maximum Entropy Coding. Xin Liu, Zhongdao Wang, Yali Li, Shengjin Wang |
| 2022 | Self-Supervised Learning with an Information Maximization Criterion. Serdar Ozsoy, Shadi Hamdan, Sercan Ö. Arik, Deniz Yuret, Alper T. Erdogan |
| 2022 | Self-Supervised Pretraining for Large-Scale Point Clouds. Zaiwei Zhang, Min Bai, Li Erran Li |
| 2022 | Self-Supervised Visual Representation Learning with Semantic Grouping. Xin Wen, Bingchen Zhao, Anlin Zheng, Xiangyu Zhang, Xiaojuan Qi |
| 2022 | Self-explaining deep models with logic rule reasoning. Seungeon Lee, Xiting Wang, Sungwon Han, Xiaoyuan Yi, Xing Xie, Meeyoung Cha |
| 2022 | Self-supervised Amodal Video Object Segmentation. Jian Yao, Yuxin Hong, Chiyu Wang, Tianjun Xiao, Tong He, Francesco Locatello, David P. Wipf, Yanwei Fu, Zheng Zhang |
| 2022 | Self-supervised Heterogeneous Graph Pre-training Based on Structural Clustering. Yaming Yang, Ziyu Guan, Zhe Wang, Wei Zhao, Cai Xu, Weigang Lu, Jianbin Huang |
| 2022 | Self-supervised surround-view depth estimation with volumetric feature fusion. Jung-Hee Kim, Junhwa Hur, Tien Phuoc Nguyen, Seong-Gyun Jeong |
| 2022 | SemMAE: Semantic-Guided Masking for Learning Masked Autoencoders. Gang Li, Heliang Zheng, Daqing Liu, Chaoyue Wang, Bing Su, Changwen Zheng |
| 2022 | Semantic Diffusion Network for Semantic Segmentation. Haoru Tan, Sitong Wu, Jimin Pi |
| 2022 | Semantic Exploration from Language Abstractions and Pretrained Representations. Allison C. Tam, Neil C. Rabinowitz, Andrew K. Lampinen, Nicholas A. Roy, Stephanie C. Y. Chan, DJ Strouse, Jane Wang, Andrea Banino, Felix Hill |
| 2022 | Semantic Probabilistic Layers for Neuro-Symbolic Learning. Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari |
| 2022 | Semantic uncertainty intervals for disentangled latent spaces. Swami Sankaranarayanan, Anastasios Angelopoulos, Stephen Bates, Yaniv Romano, Phillip Isola |
| 2022 | Semi-Discrete Normalizing Flows through Differentiable Tessellation. Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel |
| 2022 | Semi-Supervised Generative Models for Multiagent Trajectories. Dennis Fassmeyer, Pascal Fassmeyer, Ulf Brefeld |
| 2022 | Semi-Supervised Learning with Decision Trees: Graph Laplacian Tree Alternating Optimization. Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán |
| 2022 | Semi-Supervised Semantic Segmentation via Gentle Teaching Assistant. Ying Jin, Jiaqi Wang, Dahua Lin |
| 2022 | Semi-Supervised Video Salient Object Detection Based on Uncertainty-Guided Pseudo Labels. Yongri Piao, Chenyang Lu, Miao Zhang, Huchuan Lu |
| 2022 | Semi-infinitely Constrained Markov Decision Processes. Liangyu Zhang, Yang Peng, Wenhao Yang, Zhihua Zhang |
| 2022 | Semi-supervised Active Linear Regression. Nived Rajaraman, Devvrit, Pranjal Awasthi |
| 2022 | Semi-supervised Semantic Segmentation with Prototype-based Consistency Regularization. Haiming Xu, Lingqiao Liu, Qiuchen Bian, Zhen Yang |
| 2022 | Semi-supervised Vision Transformers at Scale. Zhaowei Cai, Avinash Ravichandran, Paolo Favaro, Manchen Wang, Davide Modolo, Rahul Bhotika, Zhuowen Tu, Stefano Soatto |
| 2022 | SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training. Enmao Diao, Jie Ding, Vahid Tarokh |
| 2022 | SeqPATE: Differentially Private Text Generation via Knowledge Distillation. Zhiliang Tian, Yingxiu Zhao, Ziyue Huang, Yu-Xiang Wang, Nevin L. Zhang, He He |
| 2022 | Sequence Model Imitation Learning with Unobserved Contexts. Gokul Swamy, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu |
| 2022 | Sequence-to-Set Generative Models. Longtao Tang, Ying Zhou, Yu Yang |
| 2022 | Sequencer: Deep LSTM for Image Classification. Yuki Tatsunami, Masato Taki |
| 2022 | Sequential Information Design: Learning to Persuade in the Dark. Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti, Francesco Trovò |
| 2022 | Set-based Meta-Interpolation for Few-Task Meta-Learning. Seanie Lee, Bruno Andreis, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang |
| 2022 | Shadow Knowledge Distillation: Bridging Offline and Online Knowledge Transfer. Lujun Li, Zhe Jin |
| 2022 | Shape And Structure Preserving Differential Privacy. Carlos Soto, Karthik Bharath, Matthew Reimherr, Aleksandra B. Slavkovic |
| 2022 | Shape, Light, and Material Decomposition from Images using Monte Carlo Rendering and Denoising. Jon Hasselgren, Nikolai Hofmann, Jacob Munkberg |
| 2022 | ShapeCrafter: A Recursive Text-Conditioned 3D Shape Generation Model. Rao Fu, Xiao Zhan, Yiwen Chen, Daniel Ritchie, Srinath Sridhar |
| 2022 | Sharing Knowledge for Meta-learning with Feature Descriptions. Tomoharu Iwata, Atsutoshi Kumagai |
| 2022 | Sharp Analysis of Stochastic Optimization under Global Kurdyka-Lojasiewicz Inequality. Ilyas Fatkhullin, Jalal Etesami, Niao He, Negar Kiyavash |
| 2022 | Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning. Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi |
| 2022 | Sharpness-Aware Training for Free. Jiawei Du, Daquan Zhou, Jiashi Feng, Vincent Y. F. Tan, Joey Tianyi Zhou |
| 2022 | Shield Decentralization for Safe Multi-Agent Reinforcement Learning. Daniel Melcer, Christopher Amato, Stavros Tripakis |
| 2022 | ShuffleMixer: An Efficient ConvNet for Image Super-Resolution. Long Sun, Jinshan Pan, Jinhui Tang |
| 2022 | SignRFF: Sign Random Fourier Features. Xiaoyun Li, Ping Li |
| 2022 | Signal Processing for Implicit Neural Representations. Dejia Xu, Peihao Wang, Yifan Jiang, Zhiwen Fan, Zhangyang Wang |
| 2022 | Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse. Lorenzo Noci, Sotiris Anagnostidis, Luca Biggio, Antonio Orvieto, Sidak Pal Singh, Aurélien Lucchi |
| 2022 | Signal Recovery with Non-Expansive Generative Network Priors. Jorio Cocola |
| 2022 | Simple Mechanisms for Welfare Maximization in Rich Advertising Auctions. Gagan Aggarwal, Kshipra Bhawalkar, Aranyak Mehta, Divyarthi Mohan, Alexandros Psomas |
| 2022 | Simple Unsupervised Object-Centric Learning for Complex and Naturalistic Videos. Gautam Singh, Yi-Fu Wu, Sungjin Ahn |
| 2022 | Simple and Optimal Greedy Online Contention Resolution Schemes. Vasilis Livanos |
| 2022 | Simplified Graph Convolution with Heterophily. Sudhanshu Chanpuriya, Cameron Musco |
| 2022 | Simulation-guided Beam Search for Neural Combinatorial Optimization. Jinho Choo, Yeong-Dae Kwon, Jihoon Kim, Jeongwoo Jae, André Hottung, Kevin Tierney, Youngjune Gwon |
| 2022 | Simultaneous Missing Value Imputation and Structure Learning with Groups. Pablo Morales-Alvarez, Wenbo Gong, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Nick Pawlowski, Miltiadis Allamanis, Cheng Zhang |
| 2022 | Single Loop Gaussian Homotopy Method for Non-convex Optimization. Hidenori Iwakiri, Yuhang Wang, Shinji Ito, Akiko Takeda |
| 2022 | Single Model Uncertainty Estimation via Stochastic Data Centering. Jayaraman J. Thiagarajan, Rushil Anirudh, Vivek Sivaraman Narayanaswamy, Timo Bremer |
| 2022 | Single-Stage Visual Relationship Learning using Conditional Queries. Alakh Desai, Tz-Ying Wu, Subarna Tripathi, Nuno Vasconcelos |
| 2022 | Single-pass Streaming Lower Bounds for Multi-armed Bandits Exploration with Instance-sensitive Sample Complexity. Sepehr Assadi, Chen Wang |
| 2022 | Single-phase deep learning in cortico-cortical networks. Will Greedy, Heng Wei Zhu, Joseph Pemberton, Jack Mellor, Rui Ponte Costa |
| 2022 | Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning. Yanpeng Sun, Qiang Chen, Xiangyu He, Jian Wang, Haocheng Feng, Junyu Han, Errui Ding, Jian Cheng, Zechao Li, Jingdong Wang |
| 2022 | Size and depth of monotone neural networks: interpolation and approximation. Dan Mikulincer, Daniel Reichman |
| 2022 | SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks. Davide Buffelli, Pietro Lió, Fabio Vandin |
| 2022 | Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity. Mucong Ding, Tahseen Rabbani, Bang An, Evan Wang, Furong Huang |
| 2022 | SketchBoost: Fast Gradient Boosted Decision Tree for Multioutput Problems. Leonid Iosipoi, Anton Vakhrushev |
| 2022 | Sketching based Representations for Robust Image Classification with Provable Guarantees. Nishanth Dikkala, Sankeerth Rao Karingula, Raghu Meka, Jelani Nelson, Rina Panigrahy, Xin Wang |
| 2022 | Skills Regularized Task Decomposition for Multi-task Offline Reinforcement Learning. Minjong Yoo, Sangwoo Cho, Honguk Woo |
| 2022 | SkinCon: A skin disease dataset densely annotated by domain experts for fine-grained debugging and analysis. Roxana Daneshjou, Mert Yüksekgönül, Zhuo Ran Cai, Roberto A. Novoa, James Y. Zou |
| 2022 | Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from Scratch. Hossein Souri, Liam Fowl, Rama Chellappa, Micah Goldblum, Tom Goldstein |
| 2022 | Smooth Fictitious Play in Stochastic Games with Perturbed Payoffs and Unknown Transitions. Lucas Baudin, Rida Laraki |
| 2022 | Smoothed Embeddings for Certified Few-Shot Learning. Mikhail Pautov, Olesya Kuznetsova, Nurislam Tursynbek, Aleksandr Petiushko, Ivan V. Oseledets |
| 2022 | Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor. Lijun Zhang, Wei Jiang, Jinfeng Yi, Tianbao Yang |
| 2022 | SnAKe: Bayesian Optimization with Pathwise Exploration. Jose Pablo Folch, Shiqiang Zhang, Robert M. Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener |
| 2022 | So3krates: Equivariant attention for interactions on arbitrary length-scales in molecular systems. J. Thorben Frank, Oliver T. Unke, Klaus-Robert Müller |
| 2022 | SoLar: Sinkhorn Label Refinery for Imbalanced Partial-Label Learning. Haobo Wang, Mingxuan Xia, Yixuan Li, Yuren Mao, Lei Feng, Gang Chen, Junbo Zhao |
| 2022 | Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent. Yiping Lu, José H. Blanchet, Lexing Ying |
| 2022 | Social-Inverse: Inverse Decision-making of Social Contagion Management with Task Migrations. Guangmo Tong |
| 2022 | Society of Agents: Regret Bounds of Concurrent Thompson Sampling. Yan Chen, Perry Dong, Qinxun Bai, Maria Dimakopoulou, Wei Xu, Zhengyuan Zhou |
| 2022 | SoftPatch: Unsupervised Anomaly Detection with Noisy Data. Xi Jiang, Jianlin Liu, Jinbao Wang, Qiang Nie, Kai Wu, Yong Liu, Chengjie Wang, Feng Zheng |
| 2022 | Solving Quantitative Reasoning Problems with Language Models. Aitor Lewkowycz, Anders Andreassen, David Dohan, Ethan Dyer, Henryk Michalewski, Vinay V. Ramasesh, Ambrose Slone, Cem Anil, Imanol Schlag, Theo Gutman-Solo, Yuhuai Wu, Behnam Neyshabur, Guy Gur-Ari, Vedant Misra |
| 2022 | SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression. Zhize Li, Haoyu Zhao, Boyue Li, Yuejie Chi |
| 2022 | Sound and Complete Causal Identification with Latent Variables Given Local Background Knowledge. Tian-Zuo Wang, Tian Qin, Zhi-Hua Zhou |
| 2022 | Sound and Complete Verification of Polynomial Networks. Elías Abad-Rocamora, Mehmet Fatih Sahin, Fanghui Liu, Grigorios Chrysos, Volkan Cevher |
| 2022 | SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic Learning. Changan Chen, Carl Schissler, Sanchit Garg, Philip Kobernik, Alexander Clegg, Paul Calamia, Dhruv Batra, Philip W. Robinson, Kristen Grauman |
| 2022 | SparCL: Sparse Continual Learning on the Edge. Zifeng Wang, Zheng Zhan, Yifan Gong, Geng Yuan, Wei Niu, Tong Jian, Bin Ren, Stratis Ioannidis, Yanzhi Wang, Jennifer G. Dy |
| 2022 | Sparse Fourier Backpropagation in Cryo-EM Reconstruction. Dari Kimanius, Kiarash Jamali, Sjors H. W. Scheres |
| 2022 | Sparse Gaussian Process Hyperparameters: Optimize or Integrate? Vidhi Lalchand, Wessel P. Bruinsma, David R. Burt, Carl Edward Rasmussen |
| 2022 | Sparse Hypergraph Community Detection Thresholds in Stochastic Block Model. Erchuan Zhang, David Suter, Giang Truong, Syed Zulqarnain Gilani |
| 2022 | Sparse Interaction Additive Networks via Feature Interaction Detection and Sparse Selection. James Enouen, Yan Liu |
| 2022 | Sparse Probabilistic Circuits via Pruning and Growing. Meihua Dang, Anji Liu, Guy Van den Broeck |
| 2022 | Sparse Structure Search for Delta Tuning. Shengding Hu, Zhen Zhang, Ning Ding, Yadao Wang, Yasheng Wang, Zhiyuan Liu, Maosong Sun |
| 2022 | Sparse Winning Tickets are Data-Efficient Image Recognizers. Mukund Varma T., Xuxi Chen, Zhenyu Zhang, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang |
| 2022 | Sparse2Dense: Learning to Densify 3D Features for 3D Object Detection. Tianyu Wang, Xiaowei Hu, Zhengzhe Liu, Chi-Wing Fu |
| 2022 | Sparsity in Continuous-Depth Neural Networks. Hananeh Aliee, Till Richter, Mikhail Solonin, Ignacio Ibarra, Fabian J. Theis, Niki Kilbertus |
| 2022 | Spartan: Differentiable Sparsity via Regularized Transportation. Kai Sheng Tai, Tai-Peng Tian, Ser Nam Lim |
| 2022 | Spatial Mixture-of-Experts. Nikoli Dryden, Torsten Hoefler |
| 2022 | Spatial Pruned Sparse Convolution for Efficient 3D Object Detection. JianHui Liu, Yukang Chen, Xiaoqing Ye, Zhuotao Tian, Xiao Tan, Xiaojuan Qi |
| 2022 | Spectral Bias Outside the Training Set for Deep Networks in the Kernel Regime. Benjamin Bowman, Guido F. Montúfar |
| 2022 | Spectral Bias in Practice: The Role of Function Frequency in Generalization. Sara Fridovich-Keil, Raphael Gontijo Lopes, Rebecca Roelofs |
| 2022 | Spectrum Random Masking for Generalization in Image-based Reinforcement Learning. Yangru Huang, Peixi Peng, Yifan Zhao, Guangyao Chen, Yonghong Tian |
| 2022 | Spending Thinking Time Wisely: Accelerating MCTS with Virtual Expansions. Weirui Ye, Pieter Abbeel, Yang Gao |
| 2022 | Spherical Channels for Modeling Atomic Interactions. Larry Zitnick, Abhishek Das, Adeesh Kolluru, Janice Lan, Muhammed Shuaibi, Anuroop Sriram, Zachary W. Ulissi, Brandon M. Wood |
| 2022 | Spherization Layer: Representation Using Only Angles. Hoyong Kim, Kangil Kim |
| 2022 | Split-kl and PAC-Bayes-split-kl Inequalities for Ternary Random Variables. Yi-Shan Wu, Yevgeny Seldin |
| 2022 | Squeezeformer: An Efficient Transformer for Automatic Speech Recognition. Sehoon Kim, Amir Gholami, Albert E. Shaw, Nicholas Lee, Karttikeya Mangalam, Jitendra Malik, Michael W. Mahoney, Kurt Keutzer |
| 2022 | Stability Analysis and Generalization Bounds of Adversarial Training. Jiancong Xiao, Yanbo Fan, Ruoyu Sun, Jue Wang, Zhi-Quan Luo |
| 2022 | Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks. Yunwen Lei, Rong Jin, Yiming Ying |
| 2022 | Stability and Generalization for Markov Chain Stochastic Gradient Methods. Puyu Wang, Yunwen Lei, Yiming Ying, Ding-Xuan Zhou |
| 2022 | Stability and Generalization of Kernel Clustering: from Single Kernel to Multiple Kernel. Weixuan Liang, Xinwang Liu, Yong Liu, Sihang Zhou, Jun-Jie Huang, Siwei Wang, Jiyuan Liu, Yi Zhang, En Zhu |
| 2022 | Staggered Rollout Designs Enable Causal Inference Under Interference Without Network Knowledge. Mayleen Cortez, Matthew Eichhorn, Christina Lee Yu |
| 2022 | Staircase Attention for Recurrent Processing of Sequences. Da Ju, Stephen Roller, Sainbayar Sukhbaatar, Jason Weston |
| 2022 | Star Temporal Classification: Sequence Modeling with Partially Labeled Data. Vineel Pratap, Awni Hannun, Gabriel Synnaeve, Ronan Collobert |
| 2022 | Stars: Tera-Scale Graph Building for Clustering and Learning. CJ Carey, Jonathan Halcrow, Rajesh Jayaram, Vahab Mirrokni, Warren Schudy, Peilin Zhong |
| 2022 | Statistical Learning and Inverse Problems: A Stochastic Gradient Approach. Yuri R. Fonseca, Yuri F. Saporito |
| 2022 | Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances. Sloan Nietert, Ziv Goldfeld, Ritwik Sadhu, Kengo Kato |
| 2022 | Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers. Colin Wei, Yining Chen, Tengyu Ma |
| 2022 | Stimulative Training of Residual Networks: A Social Psychology Perspective of Loafing. Peng Ye, Shengji Tang, Baopu Li, Tao Chen, Wanli Ouyang |
| 2022 | Stochastic Adaptive Activation Function. Kyungsu Lee, Jaeseung Yang, Haeyun Lee, Jae Youn Hwang |
| 2022 | Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions. Xufeng Cai, Chaobing Song, Cristóbal Guzmán, Jelena Diakonikolas |
| 2022 | Stochastic Multiple Target Sampling Gradient Descent. Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung |
| 2022 | Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality. Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert |
| 2022 | Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Functions. Saeed Masiha, Saber Salehkaleybar, Niao He, Negar Kiyavash, Patrick Thiran |
| 2022 | Stochastic Window Transformer for Image Restoration. Jie Xiao, Xueyang Fu, Feng Wu, Zheng-Jun Zha |
| 2022 | Streaming Radiance Fields for 3D Video Synthesis. Lingzhi Li, Zhen Shen, Zhongshu Wang, Li Shen, Ping Tan |
| 2022 | StrokeRehab: A Benchmark Dataset for Sub-second Action Identification. Aakash Kaku, Kangning Liu, Avinash Parnandi, Haresh Rengaraj Rajamohan, Kannan Venkataramanan, Anita Venkatesan, Audre Wirtanen, Natasha Pandit, Heidi M. Schambra, Carlos Fernandez-Granda |
| 2022 | Structural Analysis of Branch-and-Cut and the Learnability of Gomory Mixed Integer Cuts. Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik |
| 2022 | Structural Kernel Search via Bayesian Optimization and Symbolical Optimal Transport. Matthias Bitzer, Mona Meister, Christoph Zimmer |
| 2022 | Structural Knowledge Distillation for Object Detection. Philip de Rijk, Lukas Schneider, Marius Cordts, Dariu Gavrila |
| 2022 | Structural Pruning via Latency-Saliency Knapsack. Maying Shen, Hongxu Yin, Pavlo Molchanov, Lei Mao, Jianna Liu, José M. Álvarez |
| 2022 | Structure-Aware Image Segmentation with Homotopy Warping. Xiaoling Hu |
| 2022 | Structure-Preserving 3D Garment Modeling with Neural Sewing Machines. Xipeng Chen, Guangrun Wang, Dizhong Zhu, Xiaodan Liang, Philip H. S. Torr, Liang Lin |
| 2022 | Structured Energy Network As a Loss. Jay Yoon Lee, Dhruvesh Patel, Purujit Goyal, Wenlong Zhao, Zhiyang Xu, Andrew McCallum |
| 2022 | Structured Recognition for Generative Models with Explaining Away. Changmin Yu, Hugo Soulat, Neil Burgess, Maneesh Sahani |
| 2022 | Structuring Representations Using Group Invariants. Mehran Shakerinava, Arnab Kumar Mondal, Siamak Ravanbakhsh |
| 2022 | Structuring Uncertainty for Fine-Grained Sampling in Stochastic Segmentation Networks. Frank Nussbaum, Jakob Gawlikowski, Julia Niebling |
| 2022 | Sub-exponential time Sum-of-Squares lower bounds for Principal Components Analysis. Aaron Potechin, Goutham Rajendran |
| 2022 | Subgame Solving in Adversarial Team Games. Brian Hu Zhang, Luca Carminati, Federico Cacciamani, Gabriele Farina, Pierriccardo Olivieri, Nicola Gatti, Tuomas Sandholm |
| 2022 | Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation. Josh Gardner, Zoran Popovic, Ludwig Schmidt |
| 2022 | Sublinear Algorithms for Hierarchical Clustering. Arpit Agarwal, Sanjeev Khanna, Huan Li, Prathamesh Patil |
| 2022 | Submodular Maximization in Clean Linear Time. Wenxin Li, Moran Feldman, Ehsan Kazemi, Amin Karbasi |
| 2022 | Subquadratic Kronecker Regression with Applications to Tensor Decomposition. Matthew Fahrbach, Gang Fu, Mehrdad Ghadiri |
| 2022 | Subsidiary Prototype Alignment for Universal Domain Adaptation. Jogendra Nath Kundu, Suvaansh Bhambri, Akshay R. Kulkarni, Hiran Sarkar, Varun Jampani, Venkatesh Babu R. |
| 2022 | Subspace Recovery from Heterogeneous Data with Non-isotropic Noise. John C. Duchi, Vitaly Feldman, Lunjia Hu, Kunal Talwar |
| 2022 | Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap. Luca Pesce, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová |
| 2022 | Supervised Training of Conditional Monge Maps. Charlotte Bunne, Andreas Krause, Marco Cuturi |
| 2022 | Supervising the Multi-Fidelity Race of Hyperparameter Configurations. Martin Wistuba, Arlind Kadra, Josif Grabocka |
| 2022 | Support Recovery in Sparse PCA with Incomplete Data. Hanbyul Lee, Qifan Song, Jean Honorio |
| 2022 | Supported Policy Optimization for Offline Reinforcement Learning. Jialong Wu, Haixu Wu, Zihan Qiu, Jianmin Wang, Mingsheng Long |
| 2022 | SurDis: A Surface Discontinuity Dataset for Wearable Technology to Assist Blind Navigation in Urban Environments. Kuan Yew Leong, Siew Mooi Lim |
| 2022 | Surprise Minimizing Multi-Agent Learning with Energy-based Models. Karush Suri, Xiao Qi Shi, Konstantinos N. Plataniotis, Yuri A. Lawryshyn |
| 2022 | Surprising Instabilities in Training Deep Networks and a Theoretical Analysis. Yuxin Sun, Dong Lao, Ganesh Sundaramoorthi, Anthony J. Yezzi |
| 2022 | Sustainable Online Reinforcement Learning for Auto-bidding. Zhiyu Mou, Yusen Huo, Rongquan Bai, Mingzhou Xie, Chuan Yu, Jian Xu, Bo Zheng |
| 2022 | SwinTrack: A Simple and Strong Baseline for Transformer Tracking. Liting Lin, Heng Fan, Zhipeng Zhang, Yong Xu, Haibin Ling |
| 2022 | Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization. Minsu Kim, Junyoung Park, Jinkyoo Park |
| 2022 | Symbolic Distillation for Learned TCP Congestion Control. S. P. Sharan, Wenqing Zheng, Kuo-Feng Hsu, Jiarong Xing, Ang Chen, Zhangyang Wang |
| 2022 | Symmetry Teleportation for Accelerated Optimization. Bo Zhao, Nima Dehmamy, Robin Walters, Rose Yu |
| 2022 | Symmetry-induced Disentanglement on Graphs. Giangiacomo Mercatali, André Freitas, Vikas Garg |
| 2022 | Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data. Yusuke Tanaka, Tomoharu Iwata, Naonori Ueda |
| 2022 | Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms. Qin Ding, Yue Kang, Yi-Wei Liu, Thomas Chun Man Lee, Cho-Jui Hsieh, James Sharpnack |
| 2022 | Synergy-of-Experts: Collaborate to Improve Adversarial Robustness. Sen Cui, Jingfeng Zhang, Jian Liang, Bo Han, Masashi Sugiyama, Changshui Zhang |
| 2022 | Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble Learning. Alex J. Chan, Mihaela van der Schaar |
| 2022 | Systematic improvement of neural network quantum states using Lanczos. Hongwei Chen, Douglas Hendry, Phillip Weinberg, Adrian E. Feiguin |
| 2022 | TA-GATES: An Encoding Scheme for Neural Network Architectures. Xuefei Ning, Zixuan Zhou, Junbo Zhao, Tianchen Zhao, Yiping Deng, Changcheng Tang, Shuang Liang, Huazhong Yang, Yu Wang |
| 2022 | TA-MoE: Topology-Aware Large Scale Mixture-of-Expert Training. Chang Chen, Min Li, Zhihua Wu, Dianhai Yu, Chao Yang |
| 2022 | TANGO: Text-driven Photorealistic and Robust 3D Stylization via Lighting Decomposition. Yongwei Chen, Rui Chen, Jiabao Lei, Yabin Zhang, Kui Jia |
| 2022 | TANKBind: Trigonometry-Aware Neural NetworKs for Drug-Protein Binding Structure Prediction. Wei Lu, Qifeng Wu, Jixian Zhang, Jiahua Rao, Chengtao Li, Shuangjia Zheng |
| 2022 | TAP-Vid: A Benchmark for Tracking Any Point in a Video. Carl Doersch, Ankush Gupta, Larisa Markeeva, Adrià Recasens, Lucas Smaira, Yusuf Aytar, João Carreira, Andrew Zisserman, Yi Yang |
| 2022 | TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels. Yaodong Yu, Alexander Wei, Sai Praneeth Karimireddy, Yi Ma, Michael I. Jordan |
| 2022 | TGEA 2.0: A Large-Scale Diagnostically Annotated Dataset with Benchmark Tasks for Text Generation of Pretrained Language Models. Huibin Ge, Xiaohu Zhao, Chuang Liu, Yulong Zeng, Qun Liu, Deyi Xiong |
| 2022 | TOIST: Task Oriented Instance Segmentation Transformer with Noun-Pronoun Distillation. Pengfei Li, Beiwen Tian, Yongliang Shi, Xiaoxue Chen, Hao Zhao, Guyue Zhou, Ya-Qin Zhang |
| 2022 | TPU-KNN: K Nearest Neighbor Search at Peak FLOP/s. Felix Chern, Blake Hechtman, Andy Davis, Ruiqi Guo, David Majnemer, Sanjiv Kumar |
| 2022 | TREC: Transient Redundancy Elimination-based Convolution. Jiawei Guan, Feng Zhang, Jiesong Liu, Hsin-Hsuan Sung, Ruofan Wu, Xiaoyong Du, Xipeng Shen |
| 2022 | TTOpt: A Maximum Volume Quantized Tensor Train-based Optimization and its Application to Reinforcement Learning. Konstantin Sozykin, Andrei Chertkov, Roman Schutski, Anh-Huy Phan, Andrzej S. Cichocki, Ivan V. Oseledets |
| 2022 | TUSK: Task-Agnostic Unsupervised Keypoints. Yuhe Jin, Weiwei Sun, Jan Hosang, Eduard Trulls, Kwang Moo Yi |
| 2022 | TVLT: Textless Vision-Language Transformer. Zineng Tang, Jaemin Cho, Yixin Nie, Mohit Bansal |
| 2022 | TaSIL: Taylor Series Imitation Learning. Daniel Pfrommer, Thomas T. C. K. Zhang, Stephen Tu, Nikolai Matni |
| 2022 | TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets. Chengrun Yang, Gabriel Bender, Hanxiao Liu, Pieter-Jan Kindermans, Madeleine Udell, Yifeng Lu, Quoc V. Le, Da Huang |
| 2022 | TaiSu: A 166M Large-scale High-Quality Dataset for Chinese Vision-Language Pre-training. Yulong Liu, Guibo Zhu, Bin Zhu, Qi Song, Guojing Ge, Haoran Chen, Guanhui Qiao, Ru Peng, Lingxiang Wu, Jinqiao Wang |
| 2022 | Taming Fat-Tailed ("Heavier-Tailed" with Potentially Infinite Variance) Noise in Federated Learning. Haibo Yang, Peiwen Qiu, Jia Liu |
| 2022 | TarGF: Learning Target Gradient Field to Rearrange Objects without Explicit Goal Specification. Mingdong Wu, Fangwei Zhong, Yulong Xia, Hao Dong |
| 2022 | Target alignment in truncated kernel ridge regression. Arash A. Amini, Richard Baumgartner, Dai Feng |
| 2022 | Task Discovery: Finding the Tasks that Neural Networks Generalize on. Andrei Atanov, Andrei Filatov, Teresa Yeo, Ajay Sohmshetty, Amir Zamir |
| 2022 | Task-Agnostic Graph Explanations. Yaochen Xie, Sumeet Katariya, Xianfeng Tang, Edward W. Huang, Nikhil Rao, Karthik Subbian, Shuiwang Ji |
| 2022 | Task-Free Continual Learning via Online Discrepancy Distance Learning. Fei Ye, Adrian G. Bors |
| 2022 | Task-level Differentially Private Meta Learning. Xinyu Zhou, Raef Bassily |
| 2022 | Teach Less, Learn More: On the Undistillable Classes in Knowledge Distillation. Yichen Zhu, Ning Liu, Zhiyuan Xu, Xin Liu, Weibin Meng, Louis Wang, Zhicai Ou, Jian Tang |
| 2022 | Teacher Forcing Recovers Reward Functions for Text Generation. Yongchang Hao, Yuxin Liu, Lili Mou |
| 2022 | TempEL: Linking Dynamically Evolving and Newly Emerging Entities. Klim Zaporojets, Lucie-Aimée Kaffee, Johannes Deleu, Thomas Demeester, Chris Develder, Isabelle Augenstein |
| 2022 | Template based Graph Neural Network with Optimal Transport Distances. Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty |
| 2022 | Tempo: Accelerating Transformer-Based Model Training through Memory Footprint Reduction. Muralidhar Andoorveedu, Zhanda Zhu, Bojian Zheng, Gennady Pekhimenko |
| 2022 | Temporal Effective Batch Normalization in Spiking Neural Networks. Chaoteng Duan, Jianhao Ding, Shiyan Chen, Zhaofei Yu, Tiejun Huang |
| 2022 | Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning. Aniket Didolkar, Kshitij Gupta, Anirudh Goyal, Nitesh B. Gundavarapu, Alex Lamb, Nan Rosemary Ke, Yoshua Bengio |
| 2022 | Temporally Disentangled Representation Learning. Weiran Yao, Guangyi Chen, Kun Zhang |
| 2022 | Temporally-Consistent Survival Analysis. Lucas Maystre, Daniel Russo |
| 2022 | Tenrec: A Large-scale Multipurpose Benchmark Dataset for Recommender Systems. Guanghu Yuan, Fajie Yuan, Yudong Li, Beibei Kong, Shujie Li, Lei Chen, Min Yang, Chenyun Yu, Bo Hu, Zang Li, Yu Xu, Xiaohu Qie |
| 2022 | Tensor Program Optimization with Probabilistic Programs. Junru Shao, Xiyou Zhou, Siyuan Feng, Bohan Hou, Ruihang Lai, Hongyi Jin, Wuwei Lin, Masahiro Masuda, Cody Hao Yu, Tianqi Chen |
| 2022 | Tensor Wheel Decomposition and Its Tensor Completion Application. Zhong-Cheng Wu, Ting-Zhu Huang, Liang-Jian Deng, Hong-Xia Dou, Deyu Meng |
| 2022 | Test Time Adaptation via Conjugate Pseudo-labels. Sachin Goyal, Mingjie Sun, Aditi Raghunathan, J. Zico Kolter |
| 2022 | Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models. Manli Shu, Weili Nie, De-An Huang, Zhiding Yu, Tom Goldstein, Anima Anandkumar, Chaowei Xiao |
| 2022 | Test-Time Training with Masked Autoencoders. Yossi Gandelsman, Yu Sun, Xinlei Chen, Alexei A. Efros |
| 2022 | Text Classification with Born's Rule. Emanuele Guidotti, Alfio Ferrara |
| 2022 | Text-Adaptive Multiple Visual Prototype Matching for Video-Text Retrieval. Chengzhi Lin, Ancong Wu, Junwei Liang, Jun Zhang, Wenhang Ge, Wei-Shi Zheng, Chunhua Shen |
| 2022 | The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset. Hugo Laurençon, Lucile Saulnier, Thomas Wang, Christopher Akiki, Albert Villanova del Moral, Teven Le Scao, Leandro von Werra, Chenghao Mou, Eduardo González Ponferrada, Huu Nguyen, Jörg Frohberg, Mario Sasko, Quentin Lhoest, Angelina McMillan-Major, Gérard Dupont, Stella Biderman, Anna Rogers, Loubna Ben Allal, Francesco De Toni, Giada Pistilli, Olivier Nguyen, Somaieh Nikpoor, Maraim Masoud, Pierre Colombo, Javier de la Rosa, Paulo Villegas, Tristan Thrush, Shayne Longpre, Sebastian Nagel, Leon Weber, Manuel Muñoz, Jian Zhu, Daniel van Strien, Zaid Alyafeai, Khalid Almubarak, Minh Chien Vu, Itziar Gonzalez-Dios, Aitor Soroa, Kyle Lo, Manan Dey, Pedro Ortiz Suarez, Aaron Gokaslan, Shamik Bose, David Ifeoluwa Adelani, Long Phan, Hieu Tran, Ian Yu, Suhas Pai, Jenny Chim, Violette Lepercq, Suzana Ilic, Margaret Mitchell, Alexandra Sasha Luccioni, Yacine Jernite |
| 2022 | The Burer-Monteiro SDP method can fail even above the Barvinok-Pataki bound. Liam O'Carroll, Vaidehi Srinivas, Aravindan Vijayaraghavan |
| 2022 | The Curse of Unrolling: Rate of Differentiating Through Optimization. Damien Scieur, Gauthier Gidel, Quentin Bertrand, Fabian Pedregosa |
| 2022 | The Dollar Street Dataset: Images Representing the Geographic and Socioeconomic Diversity of the World. William A. Gaviria Rojas, Sudnya Frederick Diamos, Keertan Kini, David Kanter, Vijay Janapa Reddi, Cody Coleman |
| 2022 | The Effects of Regularization and Data Augmentation are Class Dependent. Randall Balestriero, Léon Bottou, Yann LeCun |
| 2022 | The First Optimal Acceleration of High-Order Methods in Smooth Convex Optimization. Dmitry Kovalev, Alexander V. Gasnikov |
| 2022 | The First Optimal Algorithm for Smooth and Strongly-Convex-Strongly-Concave Minimax Optimization. Dmitry Kovalev, Alexander V. Gasnikov |
| 2022 | The Franz-Parisi Criterion and Computational Trade-offs in High Dimensional Statistics. Afonso S. Bandeira, Ahmed El Alaoui, Samuel B. Hopkins, Tselil Schramm, Alexander S. Wein, Ilias Zadik |
| 2022 | The Gyro-Structure of Some Matrix Manifolds. Xuan Son Nguyen |
| 2022 | The Hessian Screening Rule. Johan Larsson, Jonas Wallin |
| 2022 | The Impact of Task Underspecification in Evaluating Deep Reinforcement Learning. Vindula Jayawardana, Catherine Tang, Sirui Li, Dajiang Suo, Cathy Wu |
| 2022 | The Implicit Delta Method. Nathan Kallus, James McInerney |
| 2022 | The Mechanism of Prediction Head in Non-contrastive Self-supervised Learning. Zixin Wen, Yuanzhi Li |
| 2022 | The Minority Matters: A Diversity-Promoting Collaborative Metric Learning Algorithm. Shilong Bao, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, Qingming Huang |
| 2022 | The Missing Invariance Principle found - the Reciprocal Twin of Invariant Risk Minimization. Dongsung Huh, Avinash Baidya |
| 2022 | The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning. Yunhao Tang, Rémi Munos, Mark Rowland, Bernardo Ávila Pires, Will Dabney, Marc G. Bellemare |
| 2022 | The Neural Covariance SDE: Shaped Infinite Depth-and-Width Networks at Initialization. Mufan (Bill) Li, Mihai Nica, Daniel M. Roy |
| 2022 | The Neural Testbed: Evaluating Joint Predictions. Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Morteza Ibrahimi, Dieterich Lawson, Botao Hao, Brendan O'Donoghue, Benjamin Van Roy |
| 2022 | The Phenomenon of Policy Churn. Tom Schaul, André Barreto, John Quan, Georg Ostrovski |
| 2022 | The Pitfalls of Regularization in Off-Policy TD Learning. Gaurav Manek, J. Zico Kolter |
| 2022 | The Policy-gradient Placement and Generative Routing Neural Networks for Chip Design. Ruoyu Cheng, Xianglong Lyu, Yang Li, Junjie Ye, Jianye Hao, Junchi Yan |
| 2022 | The Power and Limitation of Pretraining-Finetuning for Linear Regression under Covariate Shift. Jingfeng Wu, Difan Zou, Vladimir Braverman, Quanquan Gu, Sham M. Kakade |
| 2022 | The Privacy Onion Effect: Memorization is Relative. Nicholas Carlini, Matthew Jagielski, Chiyuan Zhang, Nicolas Papernot, Andreas Terzis, Florian Tramèr |
| 2022 | The Query Complexity of Cake Cutting. Simina Brânzei, Noam Nisan |
| 2022 | The Role of Baselines in Policy Gradient Optimization. Jincheng Mei, Wesley Chung, Valentin Thomas, Bo Dai, Csaba Szepesvári, Dale Schuurmans |
| 2022 | The Sample Complexity of One-Hidden-Layer Neural Networks. Gal Vardi, Ohad Shamir, Nati Srebro |
| 2022 | The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models. Conglong Li, Minjia Zhang, Yuxiong He |
| 2022 | The Surprising Effectiveness of PPO in Cooperative Multi-Agent Games. Chao Yu, Akash Velu, Eugene Vinitsky, Jiaxuan Gao, Yu Wang, Alexandre M. Bayen, Yi Wu |
| 2022 | The Unreasonable Effectiveness of Fully-Connected Layers for Low-Data Regimes. Peter Kocsis, Peter Súkeník, Guillem Brasó, Matthias Nießner, Laura Leal-Taixé, Ismail Elezi |
| 2022 | The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning. Xi Ye, Greg Durrett |
| 2022 | The alignment property of SGD noise and how it helps select flat minima: A stability analysis. Lei Wu, Mingze Wang, Weijie Su |
| 2022 | The computational and learning benefits of Daleian neural networks. Adam Haber, Elad Schneidman |
| 2022 | The least-control principle for local learning at equilibrium. Alexander Meulemans, Nicolas Zucchet, Seijin Kobayashi, Johannes von Oswald, João Sacramento |
| 2022 | The price of ignorance: how much does it cost to forget noise structure in low-rank matrix estimation? Jean Barbier, Tianqi Hou, Marco Mondelli, Manuel Sáenz |
| 2022 | The price of unfairness in linear bandits with biased feedback. Solenne Gaucher, Alexandra Carpentier, Christophe Giraud |
| 2022 | The trade-offs of model size in large recommendation models : 100GB to 10MB Criteo-tb DLRM model. Aditya Desai, Anshumali Shrivastava |
| 2022 | Theoretical analysis of deep neural networks for temporally dependent observations. Mingliang Ma, Abolfazl Safikhani |
| 2022 | Theoretically Better and Numerically Faster Distributed Optimization with Smoothness-Aware Quantization Techniques. Bokun Wang, Mher Safaryan, Peter Richtárik |
| 2022 | Theoretically Provable Spiking Neural Networks. Shao-Qun Zhang, Zhi-Hua Zhou |
| 2022 | Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources. Peter Lippmann, Enrique Fita Sanmartín, Fred A. Hamprecht |
| 2022 | Theseus: A Library for Differentiable Nonlinear Optimization. Luis Pineda, Taosha Fan, Maurizio Monge, Shobha Venkataraman, Paloma Sodhi, Ricky T. Q. Chen, Joseph Ortiz, Daniel DeTone, Austin S. Wang, Stuart Anderson, Jing Dong, Brandon Amos, Mustafa Mukadam |
| 2022 | Thinking Outside the Ball: Optimal Learning with Gradient Descent for Generalized Linear Stochastic Convex Optimization. Idan Amir, Roi Livni, Nati Srebro |
| 2022 | Thinned random measures for sparse graphs with overlapping communities. Federica Zoe Ricci, Michele Guindani, Erik B. Sudderth |
| 2022 | This is the way: designing and compiling LEPISZCZE, a comprehensive NLP benchmark for Polish. Lukasz Augustyniak, Kamil Tagowski, Albert Sawczyn, Denis Janiak, Roman Bartusiak, Adrian Szymczak, Arkadiusz Janz, Piotr Szymanski, Marcin Watroba, Mikolaj Morzy, Tomasz Kajdanowicz, Maciej Piasecki |
| 2022 | Thompson Sampling Efficiently Learns to Control Diffusion Processes. Mohamad Kazem Shirani Faradonbeh, Mohamad Sadegh Shirani Faradonbeh, Mohsen Bayati |
| 2022 | Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers. Albert Qiaochu Jiang, Wenda Li, Szymon Tworkowski, Konrad Czechowski, Tomasz Odrzygózdz, Piotr Milos, Yuhuai Wu, Mateja Jamnik |
| 2022 | Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret. Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu |
| 2022 | Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems. Pouria Mahdavinia, Yuyang Deng, Haochuan Li, Mehrdad Mahdavi |
| 2022 | Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with Attributes. Alessio Mazzetto, Cristina Menghini, Andrew Yuan, Eli Upfal, Stephen H. Bach |
| 2022 | Tight Mutual Information Estimation With Contrastive Fenchel-Legendre Optimization. Qing Guo, Junya Chen, Dong Wang, Yuewei Yang, Xinwei Deng, Jing Huang, Lawrence Carin, Fan Li, Chenyang Tao |
| 2022 | Tikhonov Regularization is Optimal Transport Robust under Martingale Constraints. Jiajin Li, Sirui Lin, Jose H. Blanchet, Viet Anh Nguyen |
| 2022 | Time-Conditioned Dances with Simplicial Complexes: Zigzag Filtration Curve based Supra-Hodge Convolution Networks for Time-series Forecasting. Yuzhou Chen, Yulia R. Gel, H. Vincent Poor |
| 2022 | To update or not to update? Neurons at equilibrium in deep models. Andrea Bragagnolo, Enzo Tartaglione, Marco Grangetto |
| 2022 | ToDD: Topological Compound Fingerprinting in Computer-Aided Drug Discovery. Andac Demir, Baris Coskunuzer, Yulia R. Gel, Ignacio Segovia-Dominguez, Yuzhou Chen, Bulent Kiziltan |
| 2022 | TokenMixup: Efficient Attention-guided Token-level Data Augmentation for Transformers. Hyeong Kyu Choi, Joonmyung Choi, Hyunwoo J. Kim |
| 2022 | Top Two Algorithms Revisited. Marc Jourdan, Rémy Degenne, Dorian Baudry, Rianne de Heide, Emilie Kaufmann |
| 2022 | Torsional Diffusion for Molecular Conformer Generation. Bowen Jing, Gabriele Corso, Jeffrey Chang, Regina Barzilay, Tommi S. Jaakkola |
| 2022 | TotalSelfScan: Learning Full-body Avatars from Self-Portrait Videos of Faces, Hands, and Bodies. Junting Dong, Qi Fang, Yudong Guo, Sida Peng, Qing Shuai, Xiaowei Zhou, Hujun Bao |
| 2022 | Touch and Go: Learning from Human-Collected Vision and Touch. Fengyu Yang, Chenyang Ma, Jiacheng Zhang, Jing Zhu, Wenzhen Yuan, Andrew Owens |
| 2022 | Toward Efficient Robust Training against Union of $\ell_p$ Threat Models. Gaurang Sriramanan, Maharshi Gor, Soheil Feizi |
| 2022 | Toward Equation of Motion for Deep Neural Networks: Continuous-time Gradient Descent and Discretization Error Analysis. Taiki Miyagawa |
| 2022 | Toward Robust Spiking Neural Network Against Adversarial Perturbation. Ling Liang, Kaidi Xu, Xing Hu, Lei Deng, Yuan Xie |
| 2022 | Toward Understanding Privileged Features Distillation in Learning-to-Rank. Shuo Yang, Sujay Sanghavi, Holakou Rahmanian, Jan Bakus, S. V. N. Vishwanathan |
| 2022 | Toward a realistic model of speech processing in the brain with self-supervised learning. Juliette Millet, Charlotte Caucheteux, Pierre Orhan, Yves Boubenec, Alexandre Gramfort, Ewan Dunbar, Christophe Pallier, Jean-Remi King |
| 2022 | Towards Better Evaluation for Dynamic Link Prediction. Farimah Poursafaei, Shenyang Huang, Kellin Pelrine, Reihaneh Rabbany |
| 2022 | Towards Consistency in Adversarial Classification. Laurent Meunier, Raphael Ettedgui, Rafael Pinot, Yann Chevaleyre, Jamal Atif |
| 2022 | Towards Disentangling Information Paths with Coded ResNeXt. Apostolos Avranas, Marios Kountouris |
| 2022 | Towards Diverse and Faithful One-shot Adaption of Generative Adversarial Networks. Yabo Zhang, Mingshuai Yao, Yuxiang Wei, Zhilong Ji, Jinfeng Bai, Wangmeng Zuo |
| 2022 | Towards Effective Multi-Modal Interchanges in Zero-Resource Sounding Object Localization. Yang Zhao, Chen Zhang, Haifeng Huang, Haoyuan Li, Zhou Zhao |
| 2022 | Towards Efficient 3D Object Detection with Knowledge Distillation. Jihan Yang, Shaoshuai Shi, Runyu Ding, Zhe Wang, Xiaojuan Qi |
| 2022 | Towards Efficient Post-training Quantization of Pre-trained Language Models. Haoli Bai, Lu Hou, Lifeng Shang, Xin Jiang, Irwin King, Michael R. Lyu |
| 2022 | Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning. Zaiyu Huang, Hanhui Li, Zhenyu Xie, Michael Kampffmeyer, Qingling Cai, Xiaodan Liang |
| 2022 | Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learning. Yuanpei Chen, Tianhao Wu, Shengjie Wang, Xidong Feng, Jiechuan Jiang, Zongqing Lu, Stephen McAleer, Hao Dong, Song-Chun Zhu, Yaodong Yang |
| 2022 | Towards Improving Calibration in Object Detection Under Domain Shift. Muhammad Akhtar Munir, Muhammad Haris Khan, M. Saquib Sarfraz, Mohsen Ali |
| 2022 | Towards Improving Faithfulness in Abstractive Summarization. Xiuying Chen, Mingzhe Li, Xin Gao, Xiangliang Zhang |
| 2022 | Towards Learning Universal Hyperparameter Optimizers with Transformers. Yutian Chen, Xingyou Song, Chansoo Lee, Zi Wang, Richard Zhang, David Dohan, Kazuya Kawakami, Greg Kochanski, Arnaud Doucet, Marc'Aurelio Ranzato, Sagi Perel, Nando de Freitas |
| 2022 | Towards Lightweight Black-Box Attack Against Deep Neural Networks. Chenghao Sun, Yonggang Zhang, Chaoqun Wan, Qizhou Wang, Ya Li, Tongliang Liu, Bo Han, Xinmei Tian |
| 2022 | Towards Optimal Communication Complexity in Distributed Non-Convex Optimization. Kumar Kshitij Patel, Lingxiao Wang, Blake E. Woodworth, Brian Bullins, Nati Srebro |
| 2022 | Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment. Chenxiao Yang, Qitian Wu, Qingsong Wen, Zhiqiang Zhou, Liang Sun, Junchi Yan |
| 2022 | Towards Practical Control of Singular Values of Convolutional Layers. Alexandra Senderovich, Ekaterina Bulatova, Anton Obukhov, Maxim V. Rakhuba |
| 2022 | Towards Practical Few-shot Query Sets: Transductive Minimum Description Length Inference. Ségolène Martin, Malik Boudiaf, Emilie Chouzenoux, Jean-Christophe Pesquet, Ismail Ben Ayed |
| 2022 | Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias. Zihan Liu, Yun Luo, Lirong Wu, Zicheng Liu, Stan Z. Li |
| 2022 | Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation. Arnaud Delaunoy, Joeri Hermans, François Rozet, Antoine Wehenkel, Gilles Louppe |
| 2022 | Towards Robust Blind Face Restoration with Codebook Lookup Transformer. Shangchen Zhou, Kelvin C. K. Chan, Chongyi Li, Chen Change Loy |
| 2022 | Towards Safe Reinforcement Learning with a Safety Editor Policy. Haonan Yu, Wei Xu, Haichao Zhang |
| 2022 | Towards Theoretically Inspired Neural Initialization Optimization. Yibo Yang, Hong Wang, Haobo Yuan, Zhouchen Lin |
| 2022 | Towards Trustworthy Automatic Diagnosis Systems by Emulating Doctors' Reasoning with Deep Reinforcement Learning. Arsène Fansi Tchango, Rishab Goel, Julien Martel, Zhi Wen, Gaétan Marceau-Caron, Joumana Ghosn |
| 2022 | Towards Understanding Grokking: An Effective Theory of Representation Learning. Ziming Liu, Ouail Kitouni, Niklas Nolte, Eric J. Michaud, Max Tegmark, Mike Williams |
| 2022 | Towards Understanding the Condensation of Neural Networks at Initial Training. Hanxu Zhou, Qixuan Zhou, Tao Luo, Yaoyu Zhang, Zhi-Qin John Xu |
| 2022 | Towards Understanding the Mixture-of-Experts Layer in Deep Learning. Zixiang Chen, Yihe Deng, Yue Wu, Quanquan Gu, Yuanzhi Li |
| 2022 | Towards Versatile Embodied Navigation. Hanqing Wang, Wei Liang, Luc Van Gool, Wenguan Wang |
| 2022 | Towards Video Text Visual Question Answering: Benchmark and Baseline. Minyi Zhao, Bingjia Li, Jie Wang, Wanqing Li, Wenjing Zhou, Lan Zhang, Shijie Xuyang, Zhihang Yu, Xinkun Yu, Guangze Li, Aobotao Dai, Shuigeng Zhou |
| 2022 | Towards a Standardised Performance Evaluation Protocol for Cooperative MARL. Rihab Gorsane, Omayma Mahjoub, Ruan de Kock, Roland Dubb, Siddarth Singh, Arnu Pretorius |
| 2022 | Towards a Unified Framework for Uncertainty-aware Nonlinear Variable Selection with Theoretical Guarantees. Wenying Deng, Beau Coker, Rajarshi Mukherjee, Jeremiah Z. Liu, Brent A. Coull |
| 2022 | Tracking Functional Changes in Nonstationary Signals with Evolutionary Ensemble Bayesian Model for Robust Neural Decoding. Xinyun Zhu, Yu Qi, Gang Pan, Yueming Wang |
| 2022 | Tractable Function-Space Variational Inference in Bayesian Neural Networks. Tim G. J. Rudner, Zonghao Chen, Yee Whye Teh, Yarin Gal |
| 2022 | Tractable Optimality in Episodic Latent MABs. Jeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor |
| 2022 | Trade-off between Payoff and Model Rewards in Shapley-Fair Collaborative Machine Learning. Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet |
| 2022 | Trading Off Resource Budgets For Improved Regret Bounds. Thomas Orton, Damon Falck |
| 2022 | Trading off Image Quality for Robustness is not Necessary with Regularized Deterministic Autoencoders. Amrutha Saseendran, Kathrin Skubch, Stefan Falkner, Margret Keuper |
| 2022 | Trading off Utility, Informativeness, and Complexity in Emergent Communication. Mycal Tucker, Roger Levy, Julie A. Shah, Noga Zaslavsky |
| 2022 | Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes. Maxim Kodryan, Ekaterina Lobacheva, Maksim Nakhodnov, Dmitry P. Vetrov |
| 2022 | Training Spiking Neural Networks with Event-driven Backpropagation. Yaoyu Zhu, Zhaofei Yu, Wei Fang, Xiaodong Xie, Tiejun Huang, Timothée Masquelier |
| 2022 | Training Spiking Neural Networks with Local Tandem Learning. Qu Yang, Jibin Wu, Malu Zhang, Yansong Chua, Xinchao Wang, Haizhou Li |
| 2022 | Training Subset Selection for Weak Supervision. Hunter Lang, Aravindan Vijayaraghavan, David A. Sontag |
| 2022 | Training Uncertainty-Aware Classifiers with Conformalized Deep Learning. Bat-Sheva Einbinder, Yaniv Romano, Matteo Sesia, Yanfei Zhou |
| 2022 | Training and Inference on Any-Order Autoregressive Models the Right Way. Andy Shih, Dorsa Sadigh, Stefano Ermon |
| 2022 | Training language models to follow instructions with human feedback. Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul F. Christiano, Jan Leike, Ryan Lowe |
| 2022 | Training stochastic stabilized supralinear networks by dynamics-neutral growth. Wayne Soo, Máté Lengyel |
| 2022 | Training with More Confidence: Mitigating Injected and Natural Backdoors During Training. Zhenting Wang, Hailun Ding, Juan Zhai, Shiqing Ma |
| 2022 | Trajectory Inference via Mean-field Langevin in Path Space. Lénaïc Chizat, Stephen Zhang, Matthieu Heitz, Geoffrey Schiebinger |
| 2022 | Trajectory balance: Improved credit assignment in GFlowNets. Nikolay Malkin, Moksh Jain, Emmanuel Bengio, Chen Sun, Yoshua Bengio |
| 2022 | Trajectory of Mini-Batch Momentum: Batch Size Saturation and Convergence in High Dimensions. Kiwon Lee, Andrew N. Cheng, Elliot Paquette, Courtney Paquette |
| 2022 | Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline. Penghao Wu, Xiaosong Jia, Li Chen, Junchi Yan, Hongyang Li, Yu Qiao |
| 2022 | TransBoost: Improving the Best ImageNet Performance using Deep Transduction. Omer Belhasin, Guy Bar-Shalom, Ran El-Yaniv |
| 2022 | TransTab: Learning Transferable Tabular Transformers Across Tables. Zifeng Wang, Jimeng Sun |
| 2022 | Transcormer: Transformer for Sentence Scoring with Sliding Language Modeling. Kaitao Song, Yichong Leng, Xu Tan, Yicheng Zou, Tao Qin, Dongsheng Li |
| 2022 | Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation. Ioana Bica, Mihaela van der Schaar |
| 2022 | Transferring Fairness under Distribution Shifts via Fair Consistency Regularization. Bang An, Zora Che, Mucong Ding, Furong Huang |
| 2022 | Transferring Pre-trained Multimodal Representations with Cross-modal Similarity Matching. Byoungjip Kim, Sungik Choi, Dasol Hwang, Moontae Lee, Honglak Lee |
| 2022 | Transform Once: Efficient Operator Learning in Frequency Domain. Michael Poli, Stefano Massaroli, Federico Berto, Jinkyoo Park, Tri Dao, Christopher Ré, Stefano Ermon |
| 2022 | Transformer Memory as a Differentiable Search Index. Yi Tay, Vinh Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao, Jai Prakash Gupta, Tal Schuster, William W. Cohen, Donald Metzler |
| 2022 | Transformer-based Working Memory for Multiagent Reinforcement Learning with Action Parsing. Yaodong Yang, Guangyong Chen, Weixun Wang, Xiaotian Hao, Jianye Hao, Pheng-Ann Heng |
| 2022 | Transformers from an Optimization Perspective. Yongyi Yang, Zengfeng Huang, David P. Wipf |
| 2022 | Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost. Sungjun Cho, Seonwoo Min, Jinwoo Kim, Moontae Lee, Honglak Lee, Seunghoon Hong |
| 2022 | Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture. Libin Zhu, Chaoyue Liu, Mikhail Belkin |
| 2022 | Translation-equivariant Representation in Recurrent Networks with a Continuous Manifold of Attractors. Wenhao Zhang, Ying Nian Wu, Si Wu |
| 2022 | Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork. Haotao Wang, Junyuan Hong, Aston Zhang, Jiayu Zhou, Zhangyang Wang |
| 2022 | Tree Mover's Distance: Bridging Graph Metrics and Stability of Graph Neural Networks. Ching-Yao Chuang, Stefanie Jegelka |
| 2022 | Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces. Alexander Thebelt, Calvin Tsay, Robert M. Lee, Nathan Sudermann-Merx, David Walz, Behrang Shafei, Ruth Misener |
| 2022 | TreeMoCo: Contrastive Neuron Morphology Representation Learning. Hanbo Chen, Jiawei Yang, Daniel Maxim Iascone, Lijuan Liu, Lei He, Hanchuan Peng, Jianhua Yao |
| 2022 | Triangulation candidates for Bayesian optimization. Robert B. Gramacy, Annie Sauer, Nathan Wycoff |
| 2022 | Trimmed Maximum Likelihood Estimation for Robust Generalized Linear Model. Pranjal Awasthi, Abhimanyu Das, Weihao Kong, Rajat Sen |
| 2022 | Truly Deterministic Policy Optimization. Ehsan Saleh, Saba Ghaffari, Timothy Bretl, Matthew West |
| 2022 | Truncated Matrix Power Iteration for Differentiable DAG Learning. Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Ehsan Abbasnejad, Mingming Gong, Kun Zhang, Javen Qinfeng Shi |
| 2022 | Truncated proposals for scalable and hassle-free simulation-based inference. Michael Deistler, Pedro J. Gonçalves, Jakob H. Macke |
| 2022 | Trust Region Policy Optimization with Optimal Transport Discrepancies: Duality and Algorithm for Continuous Actions. Antonio Terpin, Nicolas Lanzetti, Batuhan Yardim, Florian Dörfler, Giorgia Ramponi |
| 2022 | Trustworthy Monte Carlo. Juha Harviainen, Mikko Koivisto, Petteri Kaski |
| 2022 | Tsetlin Machine for Solving Contextual Bandit Problems. Raihan Seraj, Jivitesh Sharma, Ole-Christoffer Granmo |
| 2022 | Turbocharging Solution Concepts: Solving NEs, CEs and CCEs with Neural Equilibrium Solvers. Luke Marris, Ian Gemp, Thomas Anthony, Andrea Tacchetti, Siqi Liu, Karl Tuyls |
| 2022 | Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML Evaluation. Sérgio M. Jesus, José Pombal, Duarte M. Alves, André Ferreira Cruz, Pedro Saleiro, Rita P. Ribeiro, João Gama, Pedro Bizarro |
| 2022 | TweetNERD - End to End Entity Linking Benchmark for Tweets. Shubhanshu Mishra, Aman Saini, Raheleh Makki, Sneha Mehta, Aria Haghighi, Ali Mollahosseini |
| 2022 | TwiBot-22: Towards Graph-Based Twitter Bot Detection. Shangbin Feng, Zhaoxuan Tan, Herun Wan, Ningnan Wang, Zilong Chen, Binchi Zhang, Qinghua Zheng, Wenqian Zhang, Zhenyu Lei, Shujie Yang, Xinshun Feng, Qingyue Zhang, Hongrui Wang, Yuhan Liu, Yuyang Bai, Heng Wang, Zijian Cai, Yanbo Wang, Lijing Zheng, Zihan Ma, Jundong Li, Minnan Luo |
| 2022 | Two-Stream Network for Sign Language Recognition and Translation. Yutong Chen, Ronglai Zuo, Fangyun Wei, Yu Wu, Shujie Liu, Brian Mak |
| 2022 | Two-layer neural network on infinite dimensional data: global optimization guarantee in the mean-field regime. Naoki Nishikawa, Taiji Suzuki, Atsushi Nitanda, Denny Wu |
| 2022 | UDC: Unified DNAS for Compressible TinyML Models for Neural Processing Units. Igor Fedorov, Ramon Matas Navarro, Hokchhay Tann, Chuteng Zhou, Matthew Mattina, Paul N. Whatmough |
| 2022 | ULNeF: Untangled Layered Neural Fields for Mix-and-Match Virtual Try-On. Igor Santesteban, Miguel A. Otaduy, Nils Thuerey, Dan Casas |
| 2022 | UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup. Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao |
| 2022 | UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs. Philipp Oberdiek, Gernot A. Fink, Matthias Rottmann |
| 2022 | USB: A Unified Semi-supervised Learning Benchmark for Classification. Yidong Wang, Hao Chen, Yue Fan, Wang Sun, Ran Tao, Wenxin Hou, Renjie Wang, Linyi Yang, Zhi Zhou, Lan-Zhe Guo, Heli Qi, Zhen Wu, Yufeng Li, Satoshi Nakamura, Wei Ye, Marios Savvides, Bhiksha Raj, Takahiro Shinozaki, Bernt Schiele, Jindong Wang, Xing Xie, Yue Zhang |
| 2022 | UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes. Alexander Kolesnikov, André Susano Pinto, Lucas Beyer, Xiaohua Zhai, Jeremiah Harmsen, Neil Houlsby |
| 2022 | Uncalibrated Models Can Improve Human-AI Collaboration. Kailas Vodrahalli, Tobias Gerstenberg, James Y. Zou |
| 2022 | Uncertainty Estimation Using Riemannian Model Dynamics for Offline Reinforcement Learning. Guy Tennenholtz, Shie Mannor |
| 2022 | Uncertainty Estimation for Multi-view Data: The Power of Seeing the Whole Picture. Myong Chol Jung, He Zhao, Joanna Dipnall, Belinda Gabbe, Lan Du |
| 2022 | Uncertainty-Aware Hierarchical Refinement for Incremental Implicitly-Refined Classification. Jian Yang, Kai Zhu, Kecheng Zheng, Yang Cao |
| 2022 | Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game. Guiliang Liu, Yudong Luo, Oliver Schulte, Pascal Poupart |
| 2022 | Uncoupled Learning Dynamics with Ioannis Anagnostides, Gabriele Farina, Christian Kroer, Chung-wei Lee, Haipeng Luo, Tuomas Sandholm |
| 2022 | Uncovering the Structural Fairness in Graph Contrastive Learning. Ruijia Wang, Xiao Wang, Chuan Shi, Le Song |
| 2022 | Understanding Aesthetics with Language: A Photo Critique Dataset for Aesthetic Assessment. Daniel Vera Nieto, Luigi Celona, Clara Fernandez-Labrador |
| 2022 | Understanding Benign Overfitting in Gradient-Based Meta Learning. Lisha Chen, Songtao Lu, Tianyi Chen |
| 2022 | Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty. Jaehoon Oh, Sungnyun Kim, Namgyu Ho, Jin-Hwa Kim, Hwanjun Song, Se-Young Yun |
| 2022 | Understanding Deep Contrastive Learning via Coordinate-wise Optimization. Yuandong Tian |
| 2022 | Understanding Deep Neural Function Approximation in Reinforcement Learning via $\epsilon$-Greedy Exploration. Fanghui Liu, Luca Viano, Volkan Cevher |
| 2022 | Understanding Hyperdimensional Computing for Parallel Single-Pass Learning. Tao Yu, Yichi Zhang, Zhiru Zhang, Christopher De Sa |
| 2022 | Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective. Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li |
| 2022 | Understanding Programmatic Weak Supervision via Source-aware Influence Function. Jieyu Zhang, Haonan Wang, Cheng-Yu Hsieh, Alexander J. Ratner |
| 2022 | Understanding Robust Learning through the Lens of Representation Similarities. Christian Cianfarani, Arjun Nitin Bhagoji, Vikash Sehwag, Ben Y. Zhao, Heather Zheng, Prateek Mittal |
| 2022 | Understanding Square Loss in Training Overparametrized Neural Network Classifiers. Tianyang Hu, Jun Wang, Wenjia Wang, Zhenguo Li |
| 2022 | Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries. Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron |
| 2022 | Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation. Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang |
| 2022 | Understanding the Eluder Dimension. Gene Li, Pritish Kamath, Dylan J. Foster, Nati Srebro |
| 2022 | Understanding the Evolution of Linear Regions in Deep Reinforcement Learning. Setareh Cohan, Nam Hee Kim, David Rolnick, Michiel van de Panne |
| 2022 | Understanding the Failure of Batch Normalization for Transformers in NLP. Jiaxi Wang, Ji Wu, Lei Huang |
| 2022 | Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction. Kaifeng Lyu, Zhiyuan Li, Sanjeev Arora |
| 2022 | UnfoldML: Cost-Aware and Uncertainty-Based Dynamic 2D Prediction for Multi-Stage Classification. Yanbo Xu, Alind Khare, Glenn Matlin, Monish Ramadoss, Rishikesan Kamaleswaran, Chao Zhang, Alexey Tumanov |
| 2022 | Uni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional MoEs. Jinguo Zhu, Xizhou Zhu, Wenhai Wang, Xiaohua Wang, Hongsheng Li, Xiaogang Wang, Jifeng Dai |
| 2022 | UniCLIP: Unified Framework for Contrastive Language-Image Pre-training. Janghyeon Lee, Jongsuk Kim, Hyounguk Shon, Bumsoo Kim, Seung Hwan Kim, Honglak Lee, Junmo Kim |
| 2022 | UniGAN: Reducing Mode Collapse in GANs using a Uniform Generator. Ziqi Pan, Li Niu, Liqing Zhang |
| 2022 | Uni[MASK]: Unified Inference in Sequential Decision Problems. Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin |
| 2022 | Unified Optimal Transport Framework for Universal Domain Adaptation. Wanxing Chang, Ye Shi, Hoang Tuan, Jingya Wang |
| 2022 | Unifying Voxel-based Representation with Transformer for 3D Object Detection. Yanwei Li, Yilun Chen, Xiaojuan Qi, Zeming Li, Jian Sun, Jiaya Jia |
| 2022 | Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search. Yao Shu, Zhongxiang Dai, Zhaoxuan Wu, Bryan Kian Hsiang Low |
| 2022 | Universal Rates for Interactive Learning. Steve Hanneke, Amin Karbasi, Shay Moran, Grigoris Velegkas |
| 2022 | Universality of Group Convolutional Neural Networks Based on Ridgelet Analysis on Groups. Sho Sonoda, Isao Ishikawa, Masahiro Ikeda |
| 2022 | Universally Expressive Communication in Multi-Agent Reinforcement Learning. Matthew Morris, Thomas D. Barrett, Arnu Pretorius |
| 2022 | Unknown-Aware Domain Adversarial Learning for Open-Set Domain Adaptation. JoonHo Jang, Byeonghu Na, DongHyeok Shin, Mingi Ji, Kyungwoo Song, Il-Chul Moon |
| 2022 | Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes. Joachim Hyam Rubinstein, Benjamin I. P. Rubinstein |
| 2022 | Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity. Abhishek Gupta, Aldo Pacchiano, Yuexiang Zhai, Sham M. Kakade, Sergey Levine |
| 2022 | Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems. Abishek Thangamuthu, Gunjan Kumar, Suresh Bishnoi, Ravinder Bhattoo, N. M. Anoop Krishnan, Sayan Ranu |
| 2022 | Unsupervised Adaptation from Repeated Traversals for Autonomous Driving. Yurong You, Cheng Perng Phoo, Katie Luo, Travis Zhang, Wei-Lun Chao, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger |
| 2022 | Unsupervised Causal Generative Understanding of Images. Titas Anciukevicius, Patrick Fox-Roberts, Edward Rosten, Paul Henderson |
| 2022 | Unsupervised Cross-Task Generalization via Retrieval Augmentation. Bill Yuchen Lin, Kangmin Tan, Chris Miller, Beiwen Tian, Xiang Ren |
| 2022 | Unsupervised Domain Adaptation for Semantic Segmentation using Depth Distribution. Quanliang Wu, Huajun Liu |
| 2022 | Unsupervised Image-to-Image Translation with Density Changing Regularization. Shaoan Xie, Qirong Ho, Kun Zhang |
| 2022 | Unsupervised Learning From Incomplete Measurements for Inverse Problems. Julián Tachella, Dongdong Chen, Mike E. Davies |
| 2022 | Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation. Haoyu Wang, Nan Wu, Hang Yang, Cong Hao, Pan Li |
| 2022 | Unsupervised Learning of Equivariant Structure from Sequences. Takeru Miyato, Masanori Koyama, Kenji Fukumizu |
| 2022 | Unsupervised Learning of Group Invariant and Equivariant Representations. Robin Winter, Marco Bertolini, Tuan Le, Frank Noé, Djork-Arné Clevert |
| 2022 | Unsupervised Learning of Shape Programs with Repeatable Implicit Parts. Boyang Deng, Sumith Kulal, Zhengyang Dong, Congyue Deng, Yonglong Tian, Jiajun Wu |
| 2022 | Unsupervised Learning under Latent Label Shift. Manley Roberts, Pranav Mani, Saurabh Garg, Zachary C. Lipton |
| 2022 | Unsupervised Multi-Object Segmentation by Predicting Probable Motion Patterns. Laurynas Karazija, Subhabrata Choudhury, Iro Laina, Christian Rupprecht, Andrea Vedaldi |
| 2022 | Unsupervised Multi-View Object Segmentation Using Radiance Field Propagation. Xinhang Liu, Jiaben Chen, Huai Yu, Yu-Wing Tai, Chi-Keung Tang |
| 2022 | Unsupervised Object Detection Pretraining with Joint Object Priors Generation and Detector Learning. Yizhou Wang, Meilin Chen, Shixiang Tang, Feng Zhu, Haiyang Yang, Lei Bai, Rui Zhao, Yunfeng Yan, Donglian Qi, Wanli Ouyang |
| 2022 | Unsupervised Object Representation Learning using Translation and Rotation Group Equivariant VAE. Alireza Nasiri, Tristan Bepler |
| 2022 | Unsupervised Point Cloud Completion and Segmentation by Generative Adversarial Autoencoding Network. Changfeng Ma, Yang Yang, Jie Guo, Fei Pan, Chongjun Wang, Yanwen Guo |
| 2022 | Unsupervised Reinforcement Learning with Contrastive Intrinsic Control. Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel |
| 2022 | Unsupervised Representation Learning from Pre-trained Diffusion Probabilistic Models. Zijian Zhang, Zhou Zhao, Zhijie Lin |
| 2022 | Unsupervised Skill Discovery via Recurrent Skill Training. Zheyuan Jiang, Jingyue Gao, Jianyu Chen |
| 2022 | Unsupervised Visual Representation Learning via Mutual Information Regularized Assignment. Dong Hoon Lee, Sungik Choi, Hyunwoo J. Kim, Sae-Young Chung |
| 2022 | Untargeted Backdoor Watermark: Towards Harmless and Stealthy Dataset Copyright Protection. Yiming Li, Yang Bai, Yong Jiang, Yong Yang, Shu-Tao Xia, Bo Li |
| 2022 | Uplifting Bandits. Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton |
| 2022 | Use-Case-Grounded Simulations for Explanation Evaluation. Valerie Chen, Nari Johnson, Nicholay Topin, Gregory Plumb, Ameet Talwalkar |
| 2022 | Using Embeddings for Causal Estimation of Peer Influence in Social Networks. Irina Cristali, Victor Veitch |
| 2022 | Using Mixup as a Regularizer Can Surprisingly Improve Accuracy & Out-of-Distribution Robustness. Francesco Pinto, Harry Yang, Ser Nam Lim, Philip H. S. Torr, Puneet K. Dokania |
| 2022 | Using Partial Monotonicity in Submodular Maximization. Loay Mualem, Moran Feldman |
| 2022 | Using natural language and program abstractions to instill human inductive biases in machines. Sreejan Kumar, Carlos G. Correa, Ishita Dasgupta, Raja Marjieh, Michael Y. Hu, Robert D. Hawkins, Jonathan D. Cohen, Nathaniel D. Daw, Karthik Narasimhan, Tom Griffiths |
| 2022 | VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming. Eleonora Misino, Giuseppe Marra, Emanuele Sansone |
| 2022 | VCT: A Video Compression Transformer. Fabian Mentzer, George Toderici, David Minnen, Sergi Caelles, Sung Jin Hwang, Mario Lucic, Eirikur Agustsson |
| 2022 | VER: Scaling On-Policy RL Leads to the Emergence of Navigation in Embodied Rearrangement. Erik Wijmans, Irfan Essa, Dhruv Batra |
| 2022 | VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely? Jiawei Jiang, Lukas Burkhalter, Fangcheng Fu, Bolin Ding, Bo Du, Anwar Hithnawi, Bo Li, Ce Zhang |
| 2022 | VICE: Variational Interpretable Concept Embeddings. Lukas Muttenthaler, Charles Y. Zheng, Patrick McClure, Robert A. Vandermeulen, Martin N. Hebart, Francisco Pereira |
| 2022 | VICRegL: Self-Supervised Learning of Local Visual Features. Adrien Bardes, Jean Ponce, Yann LeCun |
| 2022 | VITA: Video Instance Segmentation via Object Token Association. Miran Heo, Sukjun Hwang, Seoung Wug Oh, Joon-Young Lee, Seon Joo Kim |
| 2022 | VLMbench: A Compositional Benchmark for Vision-and-Language Manipulation. Kaizhi Zheng, Xiaotong Chen, Odest Chadwicke Jenkins, Xin Eric Wang |
| 2022 | VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts. Hangbo Bao, Wenhui Wang, Li Dong, Qiang Liu, Owais Khan Mohammed, Kriti Aggarwal, Subhojit Som, Songhao Piao, Furu Wei |
| 2022 | VRL3: A Data-Driven Framework for Visual Deep Reinforcement Learning. Che Wang, Xufang Luo, Keith W. Ross, Dongsheng Li |
| 2022 | VTC-LFC: Vision Transformer Compression with Low-Frequency Components. Zhenyu Wang, Hao Luo, Pichao Wang, Feng Ding, Fan Wang, Hao Li |
| 2022 | VaiPhy: a Variational Inference Based Algorithm for Phylogeny. Hazal Koptagel, Oskar Kviman, Harald Melin, Negar Safinianaini, Jens Lagergren |
| 2022 | Value Function Decomposition for Iterative Design of Reinforcement Learning Agents. James MacGlashan, Evan Archer, Alisa Devlic, Takuma Seno, Craig Sherstan, Peter R. Wurman, Peter Stone |
| 2022 | Variable-rate hierarchical CPC leads to acoustic unit discovery in speech. Santiago Cuervo, Adrian Lancucki, Ricard Marxer, Pawel Rychlikowski, Jan Chorowski |
| 2022 | Variance Reduced ProxSkip: Algorithm, Theory and Application to Federated Learning. Grigory Malinovsky, Kai Yi, Peter Richtárik |
| 2022 | Variational Model Perturbation for Source-Free Domain Adaptation. Mengmeng Jing, Xiantong Zhen, Jingjing Li, Cees Snoek |
| 2022 | Variational inference via Wasserstein gradient flows. Marc Lambert, Sinho Chewi, Francis R. Bach, Silvère Bonnabel, Philippe Rigollet |
| 2022 | VectorAdam for Rotation Equivariant Geometry Optimization. Selena Ling, Nicholas Sharp, Alec Jacobson |
| 2022 | VeriDark: A Large-Scale Benchmark for Authorship Verification on the Dark Web. Andrei Manolache, Florin Brad, Antonio Barbalau, Radu Tudor Ionescu, Marius Popescu |
| 2022 | Verification and search algorithms for causal DAGs. Davin Choo, Kirankumar Shiragur, Arnab Bhattacharyya |
| 2022 | Versatile Multi-stage Graph Neural Network for Circuit Representation. Shuwen Yang, Zhihao Yang, Dong Li, Yingxue Zhang, Zhanguang Zhang, Guojie Song, Jianye Hao |
| 2022 | ViSioNS: Visual Search in Natural Scenes Benchmark. Fermín Travi, Gonzalo Ruarte, Gastón Bujia, Juan E. Kamienkowski |
| 2022 | ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation. Yufei Xu, Jing Zhang, Qiming Zhang, Dacheng Tao |
| 2022 | Video Diffusion Models. Jonathan Ho, Tim Salimans, Alexey A. Gritsenko, William Chan, Mohammad Norouzi, David J. Fleet |
| 2022 | Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos. Bowen Baker, Ilge Akkaya, Peter Zhokhov, Joost Huizinga, Jie Tang, Adrien Ecoffet, Brandon Houghton, Raul Sampedro, Jeff Clune |
| 2022 | Video compression dataset and benchmark of learning-based video-quality metrics. Anastasia Antsiferova, Sergey Lavrushkin, Maksim Smirnov, Aleksandr Gushchin, Dmitriy S. Vatolin, Dmitriy L. Kulikov |
| 2022 | Video-based Human-Object Interaction Detection from Tubelet Tokens. Danyang Tu, Wei Sun, Xiongkuo Min, Guangtao Zhai, Wei Shen |
| 2022 | VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training. Zhan Tong, Yibing Song, Jue Wang, Limin Wang |
| 2022 | ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints. Yinpeng Dong, Shouwei Ruan, Hang Su, Caixin Kang, Xingxing Wei, Jun Zhu |
| 2022 | VisCo Grids: Surface Reconstruction with Viscosity and Coarea Grids. Albert Pumarola, Artsiom Sanakoyeu, Lior Yariv, Ali K. Thabet, Yaron Lipman |
| 2022 | VisFIS: Visual Feature Importance Supervision with Right-for-the-Right-Reason Objectives. Zhuofan Ying, Peter Hase, Mohit Bansal |
| 2022 | Vision GNN: An Image is Worth Graph of Nodes. Kai Han, Yunhe Wang, Jianyuan Guo, Yehui Tang, Enhua Wu |
| 2022 | Vision Transformers provably learn spatial structure. Samy Jelassi, Michael E. Sander, Yuanzhi Li |
| 2022 | Visual Clues: Bridging Vision and Language Foundations for Image Paragraph Captioning. Yujia Xie, Luowei Zhou, Xiyang Dai, Lu Yuan, Nguyen Bach, Ce Liu, Michael Zeng |
| 2022 | Visual Concepts Tokenization. Tao Yang, Yuwang Wang, Yan Lu, Nanning Zheng |
| 2022 | Visual Prompting via Image Inpainting. Amir Bar, Yossi Gandelsman, Trevor Darrell, Amir Globerson, Alexei A. Efros |
| 2022 | Visual correspondence-based explanations improve AI robustness and human-AI team accuracy. Mohammad Reza Taesiri, Giang Nguyen, Anh Nguyen |
| 2022 | VoiceBlock: Privacy through Real-Time Adversarial Attacks with Audio-to-Audio Models. Patrick O'Reilly, Andreas Bugler, Keshav Bhandari, Max Morrison, Bryan Pardo |
| 2022 | VoxGRAF: Fast 3D-Aware Image Synthesis with Sparse Voxel Grids. Katja Schwarz, Axel Sauer, Michael Niemeyer, Yiyi Liao, Andreas Geiger |
| 2022 | WT-MVSNet: Window-based Transformers for Multi-view Stereo. Jinli Liao, Yikang Ding, Yoli Shavit, Dihe Huang, Shihao Ren, Jia Guo, Wensen Feng, Kai Zhang |
| 2022 | Washing The Unwashable : On The (Im)possibility of Fairwashing Detection. Ali Shahin Shamsabadi, Mohammad Yaghini, Natalie Dullerud, Sierra Calanda Wyllie, Ulrich Aïvodji, Aisha Alaagib, Sébastien Gambs, Nicolas Papernot |
| 2022 | Wasserstein $K$-means for clustering probability distributions. Yubo Zhuang, Xiaohui Chen, Yun Yang |
| 2022 | Wasserstein Iterative Networks for Barycenter Estimation. Alexander Korotin, Vage Egiazarian, Lingxiao Li, Evgeny Burnaev |
| 2022 | Wasserstein Logistic Regression with Mixed Features. Aras Selvi, Mohammad Reza Belbasi, Martin Haugh, Wolfram Wiesemann |
| 2022 | Watermarking for Out-of-distribution Detection. Qizhou Wang, Feng Liu, Yonggang Zhang, Jing Zhang, Chen Gong, Tongliang Liu, Bo Han |
| 2022 | WaveBound: Dynamic Error Bounds for Stable Time Series Forecasting. Youngin Cho, DaeJin Kim, Dongmin Kim, Mohammad Azam Khan, Jaegul Choo |
| 2022 | Wavelet Feature Maps Compression for Image-to-Image CNNs. Shahaf E. Finder, Yair Zohav, Maor Ashkenazi, Eran Treister |
| 2022 | Wavelet Score-Based Generative Modeling. Florentin Guth, Simon Coste, Valentin De Bortoli, Stéphane Mallat |
| 2022 | Weak-shot Semantic Segmentation via Dual Similarity Transfer. Junjie Chen, Li Niu, Siyuan Zhou, Jianlou Si, Chen Qian, Liqing Zhang |
| 2022 | Weakly Supervised Representation Learning with Sparse Perturbations. Kartik Ahuja, Jason S. Hartford, Yoshua Bengio |
| 2022 | Weakly supervised causal representation learning. Johann Brehmer, Pim de Haan, Phillip Lippe, Taco S. Cohen |
| 2022 | Weakly-Supervised Multi-Granularity Map Learning for Vision-and-Language Navigation. Peihao Chen, Dongyu Ji, Kunyang Lin, Runhao Zeng, Thomas H. Li, Mingkui Tan, Chuang Gan |
| 2022 | WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents. Shunyu Yao, Howard Chen, John Yang, Karthik Narasimhan |
| 2022 | Weighted Distillation with Unlabeled Examples. Fotis Iliopoulos, Vasilis Kontonis, Cenk Baykal, Gaurav Menghani, Khoa Trinh, Erik Vee |
| 2022 | Weighted Mutual Learning with Diversity-Driven Model Compression. Miao Zhang, Li Wang, David Campos, Wei Huang, Chenjuan Guo, Bin Yang |
| 2022 | WeightedSHAP: analyzing and improving Shapley based feature attributions. Yongchan Kwon, James Y. Zou |
| 2022 | Weisfeiler and Leman Go Walking: Random Walk Kernels Revisited. Nils M. Kriege |
| 2022 | What Can Transformers Learn In-Context? A Case Study of Simple Function Classes. Shivam Garg, Dimitris Tsipras, Percy Liang, Gregory Valiant |
| 2022 | What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness? Nikolaos Tsilivis, Julia Kempe |
| 2022 | What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability Methods. Julien Colin, Thomas Fel, Rémi Cadène, Thomas Serre |
| 2022 | What Makes Graph Neural Networks Miscalibrated? Hans Hao-Hsun Hsu, Yuesong Shen, Christian Tomani, Daniel Cremers |
| 2022 | What Makes a "Good" Data Augmentation in Knowledge Distillation - A Statistical Perspective. Huan Wang, Suhas Lohit, Michael J. Jones, Yun Fu |
| 2022 | What You See is What You Classify: Black Box Attributions. Steven Stalder, Nathanaël Perraudin, Radhakrishna Achanta, Fernando Pérez-Cruz, Michele Volpi |
| 2022 | What You See is What You Get: Principled Deep Learning via Distributional Generalization. Bogdan Kulynych, Yao-Yuan Yang, Yaodong Yu, Jaroslaw Blasiok, Preetum Nakkiran |
| 2022 | What are the best Systems? New Perspectives on NLP Benchmarking. Pierre Colombo, Nathan Noiry, Ekhine Irurozki, Stéphan Clémençon |
| 2022 | What is Where by Looking: Weakly-Supervised Open-World Phrase-Grounding without Text Inputs. Tal Shaharabany, Yoad Tewel, Lior Wolf |
| 2022 | What is a Good Metric to Study Generalization of Minimax Learners? Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang |
| 2022 | What's the Harm? Sharp Bounds on the Fraction Negatively Affected by Treatment. Nathan Kallus |
| 2022 | When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture. Yichuan Mo, Dongxian Wu, Yifei Wang, Yiwen Guo, Yisen Wang |
| 2022 | When Combinatorial Thompson Sampling meets Approximation Regret. Pierre Perrault |
| 2022 | When Do Flat Minima Optimizers Work? Jean Kaddour, Linqing Liu, Ricardo Silva, Matt J. Kusner |
| 2022 | When Does Differentially Private Learning Not Suffer in High Dimensions? Xuechen Li, Daogao Liu, Tatsunori B. Hashimoto, Huseyin A. Inan, Janardhan Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta |
| 2022 | When Does Group Invariant Learning Survive Spurious Correlations? Yimeng Chen, Ruibin Xiong, Zhi-Ming Ma, Yanyan Lan |
| 2022 | When Privacy Meets Partial Information: A Refined Analysis of Differentially Private Bandits. Achraf Azize, Debabrota Basu |
| 2022 | When are Local Queries Useful for Robust Learning? Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell |
| 2022 | When are Offline Two-Player Zero-Sum Markov Games Solvable? Qiwen Cui, Simon S. Du |
| 2022 | When does dough become a bagel? Analyzing the remaining mistakes on ImageNet. Vijay Vasudevan, Benjamin Caine, Raphael Gontijo Lopes, Sara Fridovich-Keil, Rebecca Roelofs |
| 2022 | When does return-conditioned supervised learning work for offline reinforcement learning? David Brandfonbrener, Alberto Bietti, Jacob Buckman, Romain Laroche, Joan Bruna |
| 2022 | When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning. Annie Xie, Fahim Tajwar, Archit Sharma, Chelsea Finn |
| 2022 | When to Intervene: Learning Optimal Intervention Policies for Critical Events. Niranjan Damera Venkata, Chiranjib Bhattacharyya |
| 2022 | When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment. Zhijing Jin, Sydney Levine, Fernando Gonzalez Adauto, Ojasv Kamal, Maarten Sap, Mrinmaya Sachan, Rada Mihalcea, Josh Tenenbaum, Bernhard Schölkopf |
| 2022 | When to Trust Your Simulator: Dynamics-Aware Hybrid Offline-and-Online Reinforcement Learning. Haoyi Niu, Shubham Sharma, Yiwen Qiu, Ming Li, Guyue Zhou, Jianming Hu, Xianyuan Zhan |
| 2022 | When to Update Your Model: Constrained Model-based Reinforcement Learning. Tianying Ji, Yu Luo, Fuchun Sun, Mingxuan Jing, Fengxiang He, Wenbing Huang |
| 2022 | Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability. Roman Levin, Manli Shu, Eitan Borgnia, Furong Huang, Micah Goldblum, Tom Goldstein |
| 2022 | Where to Pay Attention in Sparse Training for Feature Selection? Ghada Sokar, Zahra Atashgahi, Mykola Pechenizkiy, Decebal Constantin Mocanu |
| 2022 | Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps. Yue Hu, Shaoheng Fang, Zixing Lei, Yiqi Zhong, Siheng Chen |
| 2022 | Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post Hoc Explanations. Tessa Han, Suraj Srinivas, Himabindu Lakkaraju |
| 2022 | Whitening Convergence Rate of Coupling-based Normalizing Flows. Felix Draxler, Christoph Schnörr, Ullrich Köthe |
| 2022 | Why Do Artificially Generated Data Help Adversarial Robustness. Yue Xing, Qifan Song, Guang Cheng |
| 2022 | Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power. Binghui Li, Jikai Jin, Han Zhong, John E. Hopcroft, Liwei Wang |
| 2022 | Why So Pessimistic? Estimating Uncertainties for Offline RL through Ensembles, and Why Their Independence Matters. Seyed Kamyar Seyed Ghasemipour, Shixiang Shane Gu, Ofir Nachum |
| 2022 | Why do We Need Large Batchsizes in Contrastive Learning? A Gradient-Bias Perspective. Changyou Chen, Jianyi Zhang, Yi Xu, Liqun Chen, Jiali Duan, Yiran Chen, Son Tran, Belinda Zeng, Trishul Chilimbi |
| 2022 | Why do tree-based models still outperform deep learning on typical tabular data? Léo Grinsztajn, Edouard Oyallon, Gaël Varoquaux |
| 2022 | Why neural networks find simple solutions: The many regularizers of geometric complexity. Benoit Dherin, Michael Munn, Mihaela Rosca, David Barrett |
| 2022 | Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time. Huaxiu Yao, Caroline Choi, Bochuan Cao, Yoonho Lee, Pang Wei Koh, Chelsea Finn |
| 2022 | Will Bilevel Optimizers Benefit from Loops. Kaiyi Ji, Mingrui Liu, Yingbin Liang, Lei Ying |
| 2022 | WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language Models. Yonatan Bitton, Nitzan Bitton Guetta, Ron Yosef, Yuval Elovici, Mohit Bansal, Gabriel Stanovsky, Roy Schwartz |
| 2022 | Wukong: A 100 Million Large-scale Chinese Cross-modal Pre-training Benchmark. Jiaxi Gu, Xiaojun Meng, Guansong Lu, Lu Hou, Niu Minzhe, Xiaodan Liang, Lewei Yao, Runhui Huang, Wei Zhang, Xin Jiang, Chunjing Xu, Hang Xu |
| 2022 | XTC: Extreme Compression for Pre-trained Transformers Made Simple and Efficient. Xiaoxia Wu, Zhewei Yao, Minjia Zhang, Conglong Li, Yuxiong He |
| 2022 | You Can't Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments. Keiran Paster, Sheila A. McIlraith, Jimmy Ba |
| 2022 | You Never Stop Dancing: Non-freezing Dance Generation via Bank-constrained Manifold Projection. Jiangxin Sun, Chunyu Wang, Huang Hu, Hanjiang Lai, Zhi Jin, Jian-Fang Hu |
| 2022 | You Only Live Once: Single-Life Reinforcement Learning. Annie S. Chen, Archit Sharma, Sergey Levine, Chelsea Finn |
| 2022 | Your Out-of-Distribution Detection Method is Not Robust! Mohammad Azizmalayeri, Arshia Soltani Moakhar, Arman Zarei, Reihaneh Zohrabi, Mohammad Taghi Manzuri, Mohammad Hossein Rohban |
| 2022 | Your Transformer May Not be as Powerful as You Expect. Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang, Di He |
| 2022 | ZARTS: On Zero-order Optimization for Neural Architecture Search. Xiaoxing Wang, Wenxuan Guo, Jianlin Su, Xiaokang Yang, Junchi Yan |
| 2022 | ZIN: When and How to Learn Invariance Without Environment Partition? Yong Lin, Shengyu Zhu, Lu Tan, Peng Cui |
| 2022 | ZSON: Zero-Shot Object-Goal Navigation using Multimodal Goal Embeddings. Arjun Majumdar, Gunjan Aggarwal, Bhavika Devnani, Judy Hoffman, Dhruv Batra |
| 2022 | Zero-Shot 3D Drug Design by Sketching and Generating. Siyu Long, Yi Zhou, Xinyu Dai, Hao Zhou |
| 2022 | Zero-Shot Video Question Answering via Frozen Bidirectional Language Models. Antoine Yang, Antoine Miech, Josef Sivic, Ivan Laptev, Cordelia Schmid |
| 2022 | Zero-Sum Stochastic Stackelberg Games. Denizalp Goktas, Sadie Zhao, Amy Greenwald |
| 2022 | Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks. Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov, Bryan Perozzi |
| 2022 | ZeroC: A Neuro-Symbolic Model for Zero-shot Concept Recognition and Acquisition at Inference Time. Tailin Wu, Megan Tjandrasuwita, Zhengxuan Wu, Xuelin Yang, Kevin Liu, Rok Sosic, Jure Leskovec |
| 2022 | ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers. Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, Xiaoxia Wu, Conglong Li, Yuxiong He |
| 2022 | Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity. William de Vazelhes, Hualin Zhang, Huimin Wu, Xiaotong Yuan, Bin Gu |
| 2022 | Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients. Hualin Zhang, Huan Xiong, Bin Gu |
| 2022 | Zonotope Domains for Lagrangian Neural Network Verification. Matt Jordan, Jonathan Hayase, Alex Dimakis, Sewoong Oh |
| 2022 | ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization. Qishi Dong, Muhammad Awais, Fengwei Zhou, Chuanlong Xie, Tianyang Hu, Yongxin Yang, Sung-Ho Bae, Zhenguo Li |
| 2022 | coVariance Neural Networks. Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro |
| 2022 | mRI: Multi-modal 3D Human Pose Estimation Dataset using mmWave, RGB-D, and Inertial Sensors. Sizhe An, Yin Li, Ümit Y. Ogras |
| 2022 | pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning. Daoyuan Chen, Dawei Gao, Weirui Kuang, Yaliang Li, Bolin Ding |
| 2022 | projUNN: efficient method for training deep networks with unitary matrices. Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd |
| 2022 | pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Models. Zitao Liu, Qiongqiong Liu, Jiahao Chen, Shuyan Huang, Jiliang Tang, Weiqi Luo |
| 2022 | u-HuBERT: Unified Mixed-Modal Speech Pretraining And Zero-Shot Transfer to Unlabeled Modality. Wei-Ning Hsu, Bowen Shi |
| 2022 | xView3-SAR: Detecting Dark Fishing Activity Using Synthetic Aperture Radar Imagery. Fernando Paolo, Tsu-ting Tim Lin, Ritwik Gupta, Bryce Goodman, Nirav Patel, Daniel Kuster, David Kroodsma, Jared Dunnmon |
| 2022 | 🏘️ ProcTHOR: Large-Scale Embodied AI Using Procedural Generation. Matt Deitke, Eli VanderBilt, Alvaro Herrasti, Luca Weihs, Kiana Ehsani, Jordi Salvador, Winson Han, Eric Kolve, Aniruddha Kembhavi, Roozbeh Mottaghi |