| 2022 | $\beta$-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap. Pengzhou Abel Wu, Kenji Fukumizu |
| 2022 | $\mathrm{SO}(2)$-Equivariant Reinforcement Learning. Dian Wang, Robin Walters, Robert Platt |
| 2022 | $\pi$BO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization. Carl Hvarfner, Danny Stoll, Artur L. F. Souza, Marius Lindauer, Frank Hutter, Luigi Nardi |
| 2022 | 8-bit Optimizers via Block-wise Quantization. Tim Dettmers, Mike Lewis, Sam Shleifer, Luke Zettlemoyer |
| 2022 | A Biologically Interpretable Graph Convolutional Network to Link Genetic Risk Pathways and Imaging Phenotypes of Disease. Sayan Ghosal, Qiang Chen, Giulio Pergola, Aaron L. Goldman, William Ulrich, Daniel R. Weinberger, Archana Venkataraman |
| 2022 | A Class of Short-term Recurrence Anderson Mixing Methods and Their Applications. Fuchao Wei, Chenglong Bao, Yang Liu |
| 2022 | A Comparison of Hamming Errors of Representative Variable Selection Methods. Tracy Ke, Longlin Wang |
| 2022 | A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion. Zhaoyang Lyu, Zhifeng Kong, Xudong Xu, Liang Pan, Dahua Lin |
| 2022 | A Deep Variational Approach to Clustering Survival Data. Laura Manduchi, Ricards Marcinkevics, Michela Carlotta Massi, Thomas J. Weikert, Alexander Sauter, Verena Gotta, Timothy Müller, Flavio Vasella, Marian C. Neidert, Marc Pfister, Bram Stieltjes, Julia E. Vogt |
| 2022 | A Fine-Grained Analysis on Distribution Shift. Olivia Wiles, Sven Gowal, Florian Stimberg, Sylvestre-Alvise Rebuffi, Ira Ktena, Krishnamurthy Dvijotham, Ali Taylan Cemgil |
| 2022 | A Fine-Tuning Approach to Belief State Modeling. Samuel Sokota, Hengyuan Hu, David J. Wu, J. Zico Kolter, Jakob Nicolaus Foerster, Noam Brown |
| 2022 | A First-Occupancy Representation for Reinforcement Learning. Ted Moskovitz, Spencer R. Wilson, Maneesh Sahani |
| 2022 | A General Analysis of Example-Selection for Stochastic Gradient Descent. Yucheng Lu, Si Yi Meng, Christopher De Sa |
| 2022 | A Generalized Weighted Optimization Method for Computational Learning and Inversion. Kui Ren, Yunan Yang, Björn Engquist |
| 2022 | A Johnson-Lindenstrauss Framework for Randomly Initialized CNNs. Ido Nachum, Jan Hazla, Michael Gastpar, Anatoly Khina |
| 2022 | A Loss Curvature Perspective on Training Instabilities of Deep Learning Models. Justin Gilmer, Behrooz Ghorbani, Ankush Garg, Sneha Kudugunta, Behnam Neyshabur, David Cardoze, George Edward Dahl, Zachary Nado, Orhan Firat |
| 2022 | A Neural Tangent Kernel Perspective of Infinite Tree Ensembles. Ryuichi Kanoh, Mahito Sugiyama |
| 2022 | A New Perspective on "How Graph Neural Networks Go Beyond Weisfeiler-Lehman?". Asiri Wijesinghe, Qing Wang |
| 2022 | A Non-Parametric Regression Viewpoint : Generalization of Overparametrized Deep RELU Network Under Noisy Observations. Namjoon Suh, Hyunouk Ko, Xiaoming Huo |
| 2022 | A Program to Build E(N)-Equivariant Steerable CNNs. Gabriele Cesa, Leon Lang, Maurice Weiler |
| 2022 | A Reduction-Based Framework for Conservative Bandits and Reinforcement Learning. Yunchang Yang, Tianhao Wu, Han Zhong, Evrard Garcelon, Matteo Pirotta, Alessandro Lazaric, Liwei Wang, Simon Shaolei Du |
| 2022 | A Relational Intervention Approach for Unsupervised Dynamics Generalization in Model-Based Reinforcement Learning. Jiaxian Guo, Mingming Gong, Dacheng Tao |
| 2022 | A Statistical Framework for Efficient Out of Distribution Detection in Deep Neural Networks. Matan Haroush, Tzviel Frostig, Ruth Heller, Daniel Soudry |
| 2022 | A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model. Jianwen Xie, Yaxuan Zhu, Jun Li, Ping Li |
| 2022 | A Theoretical Analysis on Feature Learning in Neural Networks: Emergence from Inputs and Advantage over Fixed Features. Zhenmei Shi, Junyi Wei, Yingyu Liang |
| 2022 | A Theory of Tournament Representations. Arun Rajkumar, Vishnu Veerathu, Abdul Bakey Mir |
| 2022 | A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training. Yifei Wang, Yisen Wang, Jiansheng Yang, Zhouchen Lin |
| 2022 | A Unified Wasserstein Distributional Robustness Framework for Adversarial Training. Anh Tuan Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Q. Phung |
| 2022 | A Zest of LIME: Towards Architecture-Independent Model Distances. Hengrui Jia, Hongyu Chen, Jonas Guan, Ali Shahin Shamsabadi, Nicolas Papernot |
| 2022 | A fast and accurate splitting method for optimal transport: analysis and implementation. Vien V. Mai, Jacob Lindbäck, Mikael Johansson |
| 2022 | A generalization of the randomized singular value decomposition. Nicolas Boullé, Alex Townsend |
| 2022 | A global convergence theory for deep ReLU implicit networks via over-parameterization. Tianxiang Gao, Hailiang Liu, Jia Liu, Hridesh Rajan, Hongyang Gao |
| 2022 | ADAVI: Automatic Dual Amortized Variational Inference Applied To Pyramidal Bayesian Models. Louis Rouillard, Demian Wassermann |
| 2022 | AEVA: Black-box Backdoor Detection Using Adversarial Extreme Value Analysis. Junfeng Guo, Ang Li, Cong Liu |
| 2022 | ARTEMIS: Attention-based Retrieval with Text-Explicit Matching and Implicit Similarity. Ginger Delmas, Rafael Sampaio de Rezende, Gabriela Csurka, Diane Larlus |
| 2022 | AS-MLP: An Axial Shifted MLP Architecture for Vision. Dongze Lian, Zehao Yu, Xing Sun, Shenghua Gao |
| 2022 | Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions. Nicholas Gao, Stephan Günnemann |
| 2022 | Accelerated Policy Learning with Parallel Differentiable Simulation. Jie Xu, Viktor Makoviychuk, Yashraj Narang, Fabio Ramos, Wojciech Matusik, Animesh Garg, Miles Macklin |
| 2022 | Acceleration of Federated Learning with Alleviated Forgetting in Local Training. Chencheng Xu, Zhiwei Hong, Minlie Huang, Tao Jiang |
| 2022 | Active Hierarchical Exploration with Stable Subgoal Representation Learning. Siyuan Li, Jin Zhang, Jianhao Wang, Yang Yu, Chongjie Zhang |
| 2022 | Actor-Critic Policy Optimization in a Large-Scale Imperfect-Information Game. Haobo Fu, Weiming Liu, Shuang Wu, Yijia Wang, Tao Yang, Kai Li, Junliang Xing, Bin Li, Bo Ma, Qiang Fu, Wei Yang |
| 2022 | Actor-critic is implicitly biased towards high entropy optimal policies. Yuzheng Hu, Ziwei Ji, Matus Telgarsky |
| 2022 | Ada-NETS: Face Clustering via Adaptive Neighbour Discovery in the Structure Space. Yaohua Wang, Yaobin Zhang, Fangyi Zhang, Senzhang Wang, Ming Lin, Yuqi Zhang, Xiuyu Sun |
| 2022 | AdaAug: Learning Class- and Instance-adaptive Data Augmentation Policies. Tsz-Him Cheung, Dit-Yan Yeung |
| 2022 | AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation. David Berthelot, Rebecca Roelofs, Kihyuk Sohn, Nicholas Carlini, Alexey Kurakin |
| 2022 | AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning. Biwei Huang, Fan Feng, Chaochao Lu, Sara Magliacane, Kun Zhang |
| 2022 | Adaptive Wavelet Transformer Network for 3D Shape Representation Learning. Hao Huang, Yi Fang |
| 2022 | Adversarial Retriever-Ranker for Dense Text Retrieval. Hang Zhang, Yeyun Gong, Yelong Shen, Jiancheng Lv, Nan Duan, Weizhu Chen |
| 2022 | Adversarial Robustness Through the Lens of Causality. Yonggang Zhang, Mingming Gong, Tongliang Liu, Gang Niu, Xinmei Tian, Bo Han, Bernhard Schölkopf, Kun Zhang |
| 2022 | Adversarial Support Alignment. Shangyuan Tong, Timur Garipov, Yang Zhang, Shiyu Chang, Tommi S. Jaakkola |
| 2022 | Adversarial Unlearning of Backdoors via Implicit Hypergradient. Yi Zeng, Si Chen, Won Park, Zhuoqing Mao, Ming Jin, Ruoxi Jia |
| 2022 | Adversarially Robust Conformal Prediction. Asaf Gendler, Tsui-Wei Weng, Luca Daniel, Yaniv Romano |
| 2022 | Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations. Jinyuan Jia, Binghui Wang, Xiaoyu Cao, Hongbin Liu, Neil Zhenqiang Gong |
| 2022 | AlphaZero-based Proof Cost Network to Aid Game Solving. Ti-Rong Wu, Chung-Chin Shih, Ting-Han Wei, Meng-Yu Tsai, Wei-Yuan Hsu, I-Chen Wu |
| 2022 | Amortized Implicit Differentiation for Stochastic Bilevel Optimization. Michael Arbel, Julien Mairal |
| 2022 | Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular Design. Wenhao Gao, Rocío Mercado, Connor W. Coley |
| 2022 | An Agnostic Approach to Federated Learning with Class Imbalance. Zebang Shen, Juan Cerviño, Hamed Hassani, Alejandro Ribeiro |
| 2022 | An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch. Youzhi Luo, Shuiwang Ji |
| 2022 | An Experimental Design Perspective on Model-Based Reinforcement Learning. Viraj Mehta, Biswajit Paria, Jeff Schneider, Stefano Ermon, Willie Neiswanger |
| 2022 | An Explanation of In-context Learning as Implicit Bayesian Inference. Sang Michael Xie, Aditi Raghunathan, Percy Liang, Tengyu Ma |
| 2022 | An Information Fusion Approach to Learning with Instance-Dependent Label Noise. Zhimeng Jiang, Kaixiong Zhou, Zirui Liu, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu |
| 2022 | An Operator Theoretic View On Pruning Deep Neural Networks. William T. Redman, Maria Fonoberova, Ryan Mohr, Yannis G. Kevrekidis, Igor Mezic |
| 2022 | An Unconstrained Layer-Peeled Perspective on Neural Collapse. Wenlong Ji, Yiping Lu, Yiliang Zhang, Zhun Deng, Weijie J. Su |
| 2022 | Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models. Fan Bao, Chongxuan Li, Jun Zhu, Bo Zhang |
| 2022 | Analyzing and Improving the Optimization Landscape of Noise-Contrastive Estimation. Bingbin Liu, Elan Rosenfeld, Pradeep Kumar Ravikumar, Andrej Risteski |
| 2022 | Ancestral protein sequence reconstruction using a tree-structured Ornstein-Uhlenbeck variational autoencoder. Lys Sanz Moreta, Ola Rønning, Ahmad Salim Al-Sibahi, Jotun Hein, Douglas L. Theobald, Thomas Hamelryck |
| 2022 | Anisotropic Random Feature Regression in High Dimensions. Gabriel Mel, Jeffrey Pennington |
| 2022 | Anomaly Detection for Tabular Data with Internal Contrastive Learning. Tom Shenkar, Lior Wolf |
| 2022 | Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy. Jiehui Xu, Haixu Wu, Jianmin Wang, Mingsheng Long |
| 2022 | Anti-Concentrated Confidence Bonuses For Scalable Exploration. Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade |
| 2022 | Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practice. Peihao Wang, Wenqing Zheng, Tianlong Chen, Zhangyang Wang |
| 2022 | Anytime Dense Prediction with Confidence Adaptivity. Zhuang Liu, Zhiqiu Xu, Hung-Ju Wang, Trevor Darrell, Evan Shelhamer |
| 2022 | Approximation and Learning with Deep Convolutional Models: a Kernel Perspective. Alberto Bietti |
| 2022 | Assessing Generalization of SGD via Disagreement. Yiding Jiang, Vaishnavh Nagarajan, Christina Baek, J. Zico Kolter |
| 2022 | Associated Learning: an Alternative to End-to-End Backpropagation that Works on CNN, RNN, and Transformer. Dennis Y. H. Wu, Dinan Lin, Vincent Chen, Hung-Hsuan Chen |
| 2022 | Asymmetry Learning for Counterfactually-invariant Classification in OOD Tasks. S. Chandra Mouli, Bruno Ribeiro |
| 2022 | Attacking deep networks with surrogate-based adversarial black-box methods is easy. Nicholas A. Lord, Romain Müller, Luca Bertinetto |
| 2022 | Attention-based Interpretability with Concept Transformers. Mattia Rigotti, Christoph Miksovic, Ioana Giurgiu, Thomas Gschwind, Paolo Scotton |
| 2022 | Audio Lottery: Speech Recognition Made Ultra-Lightweight, Noise-Robust, and Transferable. Shaojin Ding, Tianlong Chen, Zhangyang Wang |
| 2022 | Augmented Sliced Wasserstein Distances. Xiongjie Chen, Yongxin Yang, Yunpeng Li |
| 2022 | Auto-Transfer: Learning to Route Transferable Representations. Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar |
| 2022 | Auto-scaling Vision Transformers without Training. Wuyang Chen, Wei Huang, Xianzhi Du, Xiaodan Song, Zhangyang Wang, Denny Zhou |
| 2022 | Automated Self-Supervised Learning for Graphs. Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang |
| 2022 | Automatic Loss Function Search for Predict-Then-Optimize Problems with Strong Ranking Property. Boshi Wang, Jialin Yi, Hang Dong, Bo Qiao, Chuan Luo, Qingwei Lin |
| 2022 | Autonomous Learning of Object-Centric Abstractions for High-Level Planning. Steven James, Benjamin Rosman, George Konidaris |
| 2022 | Autonomous Reinforcement Learning: Formalism and Benchmarking. Archit Sharma, Kelvin Xu, Nikhil Sardana, Abhishek Gupta, Karol Hausman, Sergey Levine, Chelsea Finn |
| 2022 | Autoregressive Diffusion Models. Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, Tim Salimans |
| 2022 | Autoregressive Quantile Flows for Predictive Uncertainty Estimation. Phillip Si, Allan Bishop, Volodymyr Kuleshov |
| 2022 | Axiomatic Explanations for Visual Search, Retrieval, and Similarity Learning. Mark Hamilton, Scott M. Lundberg, Stephanie Fu, Lei Zhang, William T. Freeman |
| 2022 | BAM: Bayes with Adaptive Memory. Josue Nassar, Jennifer Rogers Brennan, Ben Evans, Kendall Lowrey |
| 2022 | BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesis. Max W. Y. Lam, Jun Wang, Dan Su, Dong Yu |
| 2022 | BEiT: BERT Pre-Training of Image Transformers. Hangbo Bao, Li Dong, Songhao Piao, Furu Wei |
| 2022 | Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future. Harshavardhan Kamarthi, Alexander Rodríguez, B. Aditya Prakash |
| 2022 | Backdoor Defense via Decoupling the Training Process. Kunzhe Huang, Yiming Li, Baoyuan Wu, Zhan Qin, Kui Ren |
| 2022 | BadPre: Task-agnostic Backdoor Attacks to Pre-trained NLP Foundation Models. Kangjie Chen, Yuxian Meng, Xiaofei Sun, Shangwei Guo, Tianwei Zhang, Jiwei Li, Chun Fan |
| 2022 | Bag of Instances Aggregation Boosts Self-supervised Distillation. Haohang Xu, Jiemin Fang, Xiaopeng Zhang, Lingxi Xie, Xinggang Wang, Wenrui Dai, Hongkai Xiong, Qi Tian |
| 2022 | Bandit Learning with Joint Effect of Incentivized Sampling, Delayed Sampling Feedback, and Self-Reinforcing User Preferences. Tianchen Zhou, Jia Liu, Chaosheng Dong, Yi Sun |
| 2022 | Bayesian Framework for Gradient Leakage. Mislav Balunovic, Dimitar Iliev Dimitrov, Robin Staab, Martin T. Vechev |
| 2022 | Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How. Yuning You, Yue Cao, Tianlong Chen, Zhangyang Wang, Yang Shen |
| 2022 | Bayesian Neural Network Priors Revisited. Vincent Fortuin, Adrià Garriga-Alonso, Sebastian W. Ober, Florian Wenzel, Gunnar Rätsch, Richard E. Turner, Mark van der Wilk, Laurence Aitchison |
| 2022 | Benchmarking the Spectrum of Agent Capabilities. Danijar Hafner |
| 2022 | Better Supervisory Signals by Observing Learning Paths. Yi Ren, Shangmin Guo, Danica J. Sutherland |
| 2022 | Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains. Qilong Zhang, Xiaodan Li, Yuefeng Chen, Jingkuan Song, Lianli Gao, Yuan He, Hui Xue |
| 2022 | Bi-linear Value Networks for Multi-goal Reinforcement Learning. Zhang-Wei Hong, Ge Yang, Pulkit Agrawal |
| 2022 | BiBERT: Accurate Fully Binarized BERT. Haotong Qin, Yifu Ding, Mingyuan Zhang, Qinghua Yan, Aishan Liu, Qingqing Dang, Ziwei Liu, Xianglong Liu |
| 2022 | Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions. Juncheng Dong, Simiao Ren, Yang Deng, Omar Khatib, Jordan M. Malof, Mohammadreza Soltani, Willie Padilla, Vahid Tarokh |
| 2022 | Boosted Curriculum Reinforcement Learning. Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen |
| 2022 | Boosting Randomized Smoothing with Variance Reduced Classifiers. Miklós Z. Horváth, Mark Niklas Müller, Marc Fischer, Martin T. Vechev |
| 2022 | Boosting the Certified Robustness of L-infinity Distance Nets. Bohang Zhang, Du Jiang, Di He, Liwei Wang |
| 2022 | Bootstrapped Meta-Learning. Sebastian Flennerhag, Yannick Schroecker, Tom Zahavy, Hado van Hasselt, David Silver, Satinder Singh |
| 2022 | Bootstrapping Semantic Segmentation with Regional Contrast. Shikun Liu, Shuaifeng Zhi, Edward Johns, Andrew J. Davison |
| 2022 | Bregman Gradient Policy Optimization. Feihu Huang, Shangqian Gao, Heng Huang |
| 2022 | Bridging Recommendation and Marketing via Recurrent Intensity Modeling. Yifei Ma, Ge Liu, Anoop Deoras |
| 2022 | Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Inscrutable Representations. Sarath Sreedharan, Utkarsh Soni, Mudit Verma, Siddharth Srivastava, Subbarao Kambhampati |
| 2022 | Bundle Networks: Fiber Bundles, Local Trivializations, and a Generative Approach to Exploring Many-to-one Maps. Nico Courts, Henry Kvinge |
| 2022 | Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing. Sai Praneeth Karimireddy, Lie He, Martin Jaggi |
| 2022 | C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks. Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez |
| 2022 | CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals. Cédric Rommel, Thomas Moreau, Joseph Paillard, Alexandre Gramfort |
| 2022 | CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation. Tongkun Xu, Weihua Chen, Pichao Wang, Fan Wang, Hao Li, Rong Jin |
| 2022 | CKConv: Continuous Kernel Convolution For Sequential Data. David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn |
| 2022 | CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability. Martin Mundt, Steven Lang, Quentin Delfosse, Kristian Kersting |
| 2022 | COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks. Fan Wu, Linyi Li, Huan Zhang, Bhavya Kailkhura, Krishnaram Kenthapadi, Ding Zhao, Bo Li |
| 2022 | COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation. Jongmin Lee, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez |
| 2022 | CROP: Certifying Robust Policies for Reinforcement Learning through Functional Smoothing. Fan Wu, Linyi Li, Zijian Huang, Yevgeniy Vorobeychik, Ding Zhao, Bo Li |
| 2022 | Can an Image Classifier Suffice For Action Recognition? Quanfu Fan, Chun-Fu Chen, Rameswar Panda |
| 2022 | Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views? Matthew Farrell, Blake Bordelon, Shubhendu Trivedi, Cengiz Pehlevan |
| 2022 | Capturing Structural Locality in Non-parametric Language Models. Frank F. Xu, Junxian He, Graham Neubig, Vincent Josua Hellendoorn |
| 2022 | Case-based reasoning for better generalization in textual reinforcement learning. Mattia Atzeni, Shehzaad Zuzar Dhuliawala, Keerthiram Murugesan, Mrinmaya Sachan |
| 2022 | Causal Contextual Bandits with Targeted Interventions. Chandrasekar Subramanian, Balaraman Ravindran |
| 2022 | Certified Robustness for Deep Equilibrium Models via Interval Bound Propagation. Colin Wei, J. Zico Kolter |
| 2022 | Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap. Yifei Wang, Qi Zhang, Yisen Wang, Jiansheng Yang, Zhouchen Lin |
| 2022 | Charformer: Fast Character Transformers via Gradient-based Subword Tokenization. Yi Tay, Vinh Q. Tran, Sebastian Ruder, Jai Prakash Gupta, Hyung Won Chung, Dara Bahri, Zhen Qin, Simon Baumgartner, Cong Yu, Donald Metzler |
| 2022 | Chemical-Reaction-Aware Molecule Representation Learning. Hongwei Wang, Weijiang Li, Xiaomeng Jin, Kyunghyun Cho, Heng Ji, Jiawei Han, Martin D. Burke |
| 2022 | Chunked Autoregressive GAN for Conditional Waveform Synthesis. Max Morrison, Rithesh Kumar, Kundan Kumar, Prem Seetharaman, Aaron C. Courville, Yoshua Bengio |
| 2022 | Churn Reduction via Distillation. Heinrich Jiang, Harikrishna Narasimhan, Dara Bahri, Andrew Cotter, Afshin Rostamizadeh |
| 2022 | Clean Images are Hard to Reblur: Exploiting the Ill-Posed Inverse Task for Dynamic Scene Deblurring. Seungjun Nah, Sanghyun Son, Jaerin Lee, Kyoung Mu Lee |
| 2022 | ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods. Victor Schmidt, Alexandra Luccioni, Mélisande Teng, Tianyu Zhang, Alexia Reynaud, Sunand Raghupathi, Gautier Cosne, Adrien Juraver, Vahe Vardanyan, Alex Hernández-García, Yoshua Bengio |
| 2022 | Closed-form Sample Probing for Learning Generative Models in Zero-shot Learning. Samet Çetin, Orhun Bugra Baran, Ramazan Gokberk Cinbis |
| 2022 | CoBERL: Contrastive BERT for Reinforcement Learning. Andrea Banino, Adrià Puigdomènech Badia, Jacob C. Walker, Tim Scholtes, Jovana Mitrovic, Charles Blundell |
| 2022 | CoMPS: Continual Meta Policy Search. Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn, Sergey Levine |
| 2022 | CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting. Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven C. H. Hoi |
| 2022 | CodeTrek: Flexible Modeling of Code using an Extensible Relational Representation. Pardis Pashakhanloo, Aaditya Naik, Yuepeng Wang, Hanjun Dai, Petros Maniatis, Mayur Naik |
| 2022 | Coherence-based Label Propagation over Time Series for Accelerated Active Learning. Yooju Shin, Susik Yoon, Sundong Kim, Hwanjun Song, Jae-Gil Lee, Byung Suk Lee |
| 2022 | Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods. Wenqing Zheng, Edward W. Huang, Nikhil Rao, Sumeet Katariya, Zhangyang Wang, Karthik Subbian |
| 2022 | Collapse by Conditioning: Training Class-conditional GANs with Limited Data. Mohamad Shahbazi, Martin Danelljan, Danda Pani Paudel, Luc Van Gool |
| 2022 | ComPhy: Compositional Physical Reasoning of Objects and Events from Videos. Zhenfang Chen, Kexin Yi, Yunzhu Li, Mingyu Ding, Antonio Torralba, Joshua B. Tenenbaum, Chuang Gan |
| 2022 | Communication-Efficient Actor-Critic Methods for Homogeneous Markov Games. Dingyang Chen, Yile Li, Qi Zhang |
| 2022 | Comparing Distributions by Measuring Differences that Affect Decision Making. Shengjia Zhao, Abhishek Sinha, Yutong He, Aidan Perreault, Jiaming Song, Stefano Ermon |
| 2022 | Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound. Claudio Ferrari, Mark Niklas Müller, Nikola Jovanovic, Martin T. Vechev |
| 2022 | Compositional Attention: Disentangling Search and Retrieval. Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie |
| 2022 | Compositional Training for End-to-End Deep AUC Maximization. Zhuoning Yuan, Zhishuai Guo, Nitesh V. Chawla, Tianbao Yang |
| 2022 | ConFeSS: A Framework for Single Source Cross-Domain Few-Shot Learning. Debasmit Das, Sungrack Yun, Fatih Porikli |
| 2022 | Concurrent Adversarial Learning for Large-Batch Training. Yong Liu, Xiangning Chen, Minhao Cheng, Cho-Jui Hsieh, Yang You |
| 2022 | Conditional Contrastive Learning with Kernel. Yao-Hung Hubert Tsai, Tianqin Li, Martin Q. Ma, Han Zhao, Kun Zhang, Louis-Philippe Morency, Ruslan Salakhutdinov |
| 2022 | Conditional Image Generation by Conditioning Variational Auto-Encoders. William Harvey, Saeid Naderiparizi, Frank Wood |
| 2022 | Conditional Object-Centric Learning from Video. Thomas Kipf, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Austin Stone, Sara Sabour, Georg Heigold, Rico Jonschkowski, Alexey Dosovitskiy, Klaus Greff |
| 2022 | Conditioning Sequence-to-sequence Networks with Learned Activations. Alberto Gil Couto Pimentel Ramos, Abhinav Mehrotra, Nicholas Donald Lane, Sourav Bhattacharya |
| 2022 | Connectome-constrained Latent Variable Model of Whole-Brain Neural Activity. Lu Mi, Richard Xu, Sridhama Prakhya, Albert Lin, Nir Shavit, Aravinthan D. T. Samuel, Srinivas C. Turaga |
| 2022 | Consistent Counterfactuals for Deep Models. Emily Black, Zifan Wang, Matt Fredrikson |
| 2022 | Constrained Physical-Statistics Models for Dynamical System Identification and Prediction. Jérémie Donà, Marie Déchelle, Patrick Gallinari, Marina Levy |
| 2022 | Constrained Policy Optimization via Bayesian World Models. Yarden As, Ilnura Usmanova, Sebastian Curi, Andreas Krause |
| 2022 | Constraining Linear-chain CRFs to Regular Languages. Sean Papay, Roman Klinger, Sebastian Padó |
| 2022 | Constructing Orthogonal Convolutions in an Explicit Manner. Tan Yu, Jun Li, Yunfeng Cai, Ping Li |
| 2022 | Constructing a Good Behavior Basis for Transfer using Generalized Policy Updates. Safa Alver, Doina Precup |
| 2022 | Contact Points Discovery for Soft-Body Manipulations with Differentiable Physics. Sizhe Li, Zhiao Huang, Tao Du, Hao Su, Joshua B. Tenenbaum, Chuang Gan |
| 2022 | Context-Aware Sparse Deep Coordination Graphs. Tonghan Wang, Liang Zeng, Weijun Dong, Qianlan Yang, Yang Yu, Chongjie Zhang |
| 2022 | Contextualized Scene Imagination for Generative Commonsense Reasoning. Peifeng Wang, Jonathan Zamora, Junfeng Liu, Filip Ilievski, Muhao Chen, Xiang Ren |
| 2022 | Continual Learning with Filter Atom Swapping. Zichen Miao, Ze Wang, Wei Chen, Qiang Qiu |
| 2022 | Continual Learning with Recursive Gradient Optimization. Hao Liu, Huaping Liu |
| 2022 | Continual Normalization: Rethinking Batch Normalization for Online Continual Learning. Quang Pham, Chenghao Liu, Steven C. H. Hoi |
| 2022 | Continuous-Time Meta-Learning with Forward Mode Differentiation. Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon |
| 2022 | Continuously Discovering Novel Strategies via Reward-Switching Policy Optimization. Zihan Zhou, Wei Fu, Bingliang Zhang, Yi Wu |
| 2022 | Contrastive Clustering to Mine Pseudo Parallel Data for Unsupervised Translation. Xuan-Phi Nguyen, Hongyu Gong, Yun Tang, Changhan Wang, Philipp Koehn, Shafiq R. Joty |
| 2022 | Contrastive Fine-grained Class Clustering via Generative Adversarial Networks. Yunji Kim, Jung-Woo Ha |
| 2022 | Controlling Directions Orthogonal to a Classifier. Yilun Xu, Hao He, Tianxiao Shen, Tommi S. Jaakkola |
| 2022 | Controlling the Complexity and Lipschitz Constant improves Polynomial Nets. Zhenyu Zhu, Fabian Latorre, Grigorios Chrysos, Volkan Cevher |
| 2022 | Convergent Graph Solvers. Junyoung Park, Jinhyun Choo, Jinkyoo Park |
| 2022 | Convergent and Efficient Deep Q Learning Algorithm. Zhikang T. Wang, Masahito Ueda |
| 2022 | CoordX: Accelerating Implicit Neural Representation with a Split MLP Architecture. Ruofan Liang, Hongyi Sun, Nandita Vijaykumar |
| 2022 | Coordination Among Neural Modules Through a Shared Global Workspace. Anirudh Goyal, Aniket Rajiv Didolkar, Alex Lamb, Kartikeya Badola, Nan Rosemary Ke, Nasim Rahaman, Jonathan Binas, Charles Blundell, Michael Curtis Mozer, Yoshua Bengio |
| 2022 | Counterfactual Plans under Distributional Ambiguity. Ngoc Bui, Duy Nguyen, Viet Anh Nguyen |
| 2022 | Creating Training Sets via Weak Indirect Supervision. Jieyu Zhang, Bohan Wang, Xiangchen Song, Yujing Wang, Yaming Yang, Jing Bai, Alexander Ratner |
| 2022 | Critical Points in Quantum Generative Models. Eric R. Anschuetz |
| 2022 | Cross-Domain Imitation Learning via Optimal Transport. Arnaud Fickinger, Samuel Cohen, Stuart Russell, Brandon Amos |
| 2022 | Cross-Lingual Transfer with Class-Weighted Language-Invariant Representations. Ruicheng Xian, Heng Ji, Han Zhao |
| 2022 | Cross-Trajectory Representation Learning for Zero-Shot Generalization in RL. Bogdan Mazoure, Ahmed M. Ahmed, R. Devon Hjelm, Andrey Kolobov, Patrick MacAlpine |
| 2022 | CrossBeam: Learning to Search in Bottom-Up Program Synthesis. Kensen Shi, Hanjun Dai, Kevin Ellis, Charles Sutton |
| 2022 | CrossFormer: A Versatile Vision Transformer Hinging on Cross-scale Attention. Wenxiao Wang, Lu Yao, Long Chen, Binbin Lin, Deng Cai, Xiaofei He, Wei Liu |
| 2022 | CrossMatch: Cross-Classifier Consistency Regularization for Open-Set Single Domain Generalization. Ronghang Zhu, Sheng Li |
| 2022 | CrowdPlay: Crowdsourcing Human Demonstrations for Offline Learning. Matthias Gerstgrasser, Rakshit S. Trivedi, David C. Parkes |
| 2022 | Crystal Diffusion Variational Autoencoder for Periodic Material Generation. Tian Xie, Xiang Fu, Octavian-Eugen Ganea, Regina Barzilay, Tommi S. Jaakkola |
| 2022 | Curriculum learning as a tool to uncover learning principles in the brain. Daniel R. Kepple, Rainer Engelken, Kanaka Rajan |
| 2022 | Curvature-Guided Dynamic Scale Networks for Multi-View Stereo. Khang Truong Giang, Soohwan Song, Sungho Jo |
| 2022 | CycleMLP: A MLP-like Architecture for Dense Prediction. Shoufa Chen, Enze Xie, Chongjian Ge, Runjian Chen, Ding Liang, Ping Luo |
| 2022 | D-CODE: Discovering Closed-form ODEs from Observed Trajectories. Zhaozhi Qian, Krzysztof Kacprzyk, Mihaela van der Schaar |
| 2022 | DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR. Shilong Liu, Feng Li, Hao Zhang, Xiao Yang, Xianbiao Qi, Hang Su, Jun Zhu, Lei Zhang |
| 2022 | DARA: Dynamics-Aware Reward Augmentation in Offline Reinforcement Learning. Jinxin Liu, Hongyin Zhang, Donglin Wang |
| 2022 | DEGREE: Decomposition Based Explanation for Graph Neural Networks. Qizhang Feng, Ninghao Liu, Fan Yang, Ruixiang Tang, Mengnan Du, Xia Hu |
| 2022 | DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting. Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu |
| 2022 | DISSECT: Disentangled Simultaneous Explanations via Concept Traversals. Asma Ghandeharioun, Been Kim, Chun-Liang Li, Brendan Jou, Brian Eoff, Rosalind W. Picard |
| 2022 | DIVA: Dataset Derivative of a Learning Task. Yonatan Dukler, Alessandro Achille, Giovanni Paolini, Avinash Ravichandran, Marzia Polito, Stefano Soatto |
| 2022 | DKM: Differentiable k-Means Clustering Layer for Neural Network Compression. Minsik Cho, Keivan Alizadeh-Vahid, Saurabh Adya, Mohammad Rastegari |
| 2022 | DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization. Aviral Kumar, Rishabh Agarwal, Tengyu Ma, Aaron C. Courville, George Tucker, Sergey Levine |
| 2022 | Data Efficient Language-Supervised Zero-Shot Recognition with Optimal Transport Distillation. Bichen Wu, Ruizhe Cheng, Peizhao Zhang, Tianren Gao, Joseph E. Gonzalez, Peter Vajda |
| 2022 | Data Poisoning Won't Save You From Facial Recognition. Evani Radiya-Dixit, Sanghyun Hong, Nicholas Carlini, Florian Tramèr |
| 2022 | Data-Driven Offline Optimization for Architecting Hardware Accelerators. Aviral Kumar, Amir Yazdanbakhsh, Milad Hashemi, Kevin Swersky, Sergey Levine |
| 2022 | Data-Efficient Graph Grammar Learning for Molecular Generation. Minghao Guo, Veronika Thost, Beichen Li, Payel Das, Jie Chen, Wojciech Matusik |
| 2022 | DeSKO: Stability-Assured Robust Control with a Deep Stochastic Koopman Operator. Minghao Han, Jacob Euler-Rolle, Robert K. Katzschmann |
| 2022 | Dealing with Non-Stationarity in MARL via Trust-Region Decomposition. Wenhao Li, Xiangfeng Wang, Bo Jin, Junjie Sheng, Hongyuan Zha |
| 2022 | Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach. Prashant Khanduri, Haibo Yang, Mingyi Hong, Jia Liu, Hoi-To Wai, Sijia Liu |
| 2022 | Declarative nets that are equilibrium models. Russell Tsuchida, Suk Yee Yong, Mohammad Ali Armin, Lars Petersson, Cheng Soon Ong |
| 2022 | Deconstructing the Inductive Biases of Hamiltonian Neural Networks. Nate Gruver, Marc Anton Finzi, Samuel Don Stanton, Andrew Gordon Wilson |
| 2022 | Decoupled Adaptation for Cross-Domain Object Detection. Junguang Jiang, Baixu Chen, Jianmin Wang, Mingsheng Long |
| 2022 | Deep Attentive Variational Inference. Ifigeneia Apostolopoulou, Ian Char, Elan Rosenfeld, Artur Dubrawski |
| 2022 | Deep AutoAugment. Yu Zheng, Zhi Zhang, Shen Yan, Mi Zhang |
| 2022 | Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity. Shiwei Liu, Tianlong Chen, Zahra Atashgahi, Xiaohan Chen, Ghada Sokar, Elena Mocanu, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu |
| 2022 | Deep Learning without Shortcuts: Shaping the Kernel with Tailored Rectifiers. Guodong Zhang, Aleksandar Botev, James Martens |
| 2022 | Deep Point Cloud Reconstruction. Jaesung Choe, Byeongin Joung, François Rameau, Jaesik Park, In So Kweon |
| 2022 | Deep ReLU Networks Preserve Expected Length. Boris Hanin, Ryan S. Jeong, David Rolnick |
| 2022 | Defending Against Image Corruptions Through Adversarial Augmentations. Dan Andrei Calian, Florian Stimberg, Olivia Wiles, Sylvestre-Alvise Rebuffi, András György, Timothy A. Mann, Sven Gowal |
| 2022 | Delaunay Component Analysis for Evaluation of Data Representations. Petra Poklukar, Vladislav Polianskii, Anastasiia Varava, Florian T. Pokorny, Danica Kragic |
| 2022 | DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations. Geon-Hyeong Kim, Seokin Seo, Jongmin Lee, Wonseok Jeon, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim |
| 2022 | Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization. Tolga Ergen, Arda Sahiner, Batu Ozturkler, John M. Pauly, Morteza Mardani, Mert Pilanci |
| 2022 | Demystifying Limited Adversarial Transferability in Automatic Speech Recognition Systems. Hadi Abdullah, Aditya Karlekar, Vincent Bindschaedler, Patrick Traynor |
| 2022 | Denoising Likelihood Score Matching for Conditional Score-based Data Generation. Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng, Yi-Chen Lo, Chia-Che Chang, Yu-Lun Liu, Yu-Lin Chang, Chia-Ping Chen, Chun-Yi Lee |
| 2022 | DictFormer: Tiny Transformer with Shared Dictionary. Qian Lou, Ting Hua, Yen-Chang Hsu, Yilin Shen, Hongxia Jin |
| 2022 | DiffSkill: Skill Abstraction from Differentiable Physics for Deformable Object Manipulations with Tools. Xingyu Lin, Zhiao Huang, Yunzhu Li, Joshua B. Tenenbaum, David Held, Chuang Gan |
| 2022 | Differentiable DAG Sampling. Bertrand Charpentier, Simon Kibler, Stephan Günnemann |
| 2022 | Differentiable Expectation-Maximization for Set Representation Learning. Minyoung Kim |
| 2022 | Differentiable Gradient Sampling for Learning Implicit 3D Scene Reconstructions from a Single Image. Shizhan Zhu, Sayna Ebrahimi, Angjoo Kanazawa, Trevor Darrell |
| 2022 | Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners. Ningyu Zhang, Luoqiu Li, Xiang Chen, Shumin Deng, Zhen Bi, Chuanqi Tan, Fei Huang, Huajun Chen |
| 2022 | Differentiable Scaffolding Tree for Molecule Optimization. Tianfan Fu, Wenhao Gao, Cao Xiao, Jacob Yasonik, Connor W. Coley, Jimeng Sun |
| 2022 | Differentially Private Fine-tuning of Language Models. Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin A. Inan, Gautam Kamath, Janardhan Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang |
| 2022 | Differentially Private Fractional Frequency Moments Estimation with Polylogarithmic Space. Lun Wang, Iosif Pinelis, Dawn Song |
| 2022 | Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme. Vadim Popov, Ivan Vovk, Vladimir Gogoryan, Tasnima Sadekova, Mikhail Sergeevich Kudinov, Jiansheng Wei |
| 2022 | Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching. Pierre-Alexandre Kamienny, Jean Tarbouriech, Sylvain Lamprier, Alessandro Lazaric, Ludovic Denoyer |
| 2022 | Discovering Invariant Rationales for Graph Neural Networks. Yingxin Wu, Xiang Wang, An Zhang, Xiangnan He, Tat-Seng Chua |
| 2022 | Discovering Latent Concepts Learned in BERT. Fahim Dalvi, Abdul Rafae Khan, Firoj Alam, Nadir Durrani, Jia Xu, Hassan Sajjad |
| 2022 | Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning. Chengping Rao, Pu Ren, Yang Liu, Hao Sun |
| 2022 | Discovering and Explaining the Representation Bottleneck of DNNS. Huiqi Deng, Qihan Ren, Hao Zhang, Quanshi Zhang |
| 2022 | Discrepancy-Based Active Learning for Domain Adaptation. Antoine de Mathelin, François Deheeger, Mathilde Mougeot, Nicolas Vayatis |
| 2022 | Discrete Representations Strengthen Vision Transformer Robustness. Chengzhi Mao, Lu Jiang, Mostafa Dehghani, Carl Vondrick, Rahul Sukthankar, Irfan Essa |
| 2022 | Discriminative Similarity for Data Clustering. Yingzhen Yang, Ping Li |
| 2022 | Disentanglement Analysis with Partial Information Decomposition. Seiya Tokui, Issei Sato |
| 2022 | Distilling GANs with Style-Mixed Triplets for X2I Translation with Limited Data. Yaxing Wang, Joost van de Weijer, Lu Yu, Shangling Jui |
| 2022 | Distribution Compression in Near-Linear Time. Abhishek Shetty, Raaz Dwivedi, Lester Mackey |
| 2022 | Distributional Reinforcement Learning with Monotonic Splines. Yudong Luo, Guiliang Liu, Haonan Duan, Oliver Schulte, Pascal Poupart |
| 2022 | Distributionally Robust Fair Principal Components via Geodesic Descents. Hieu Vu, Toan Tran, Man-Chung Yue, Viet Anh Nguyen |
| 2022 | Distributionally Robust Models with Parametric Likelihood Ratios. Paul Michel, Tatsunori Hashimoto, Graham Neubig |
| 2022 | Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions. Chen Zhu, Zheng Xu, Mingqing Chen, Jakub Konecný, Andrew Hard, Tom Goldstein |
| 2022 | Dive Deeper Into Integral Pose Regression. Kerui Gu, Linlin Yang, Angela Yao |
| 2022 | Divergence-aware Federated Self-Supervised Learning. Weiming Zhuang, Yonggang Wen, Shuai Zhang |
| 2022 | Diverse Client Selection for Federated Learning via Submodular Maximization. Ravikumar Balakrishnan, Tian Li, Tianyi Zhou, Nageen Himayat, Virginia Smith, Jeff A. Bilmes |
| 2022 | Divisive Feature Normalization Improves Image Recognition Performance in AlexNet. Michelle Miller, SueYeon Chung, Kenneth D. Miller |
| 2022 | Do Not Escape From the Manifold: Discovering the Local Coordinates on the Latent Space of GANs. Jaewoong Choi, Junho Lee, Changyeon Yoon, Jung Ho Park, Geonho Hwang, Myungjoo Kang |
| 2022 | Do Users Benefit From Interpretable Vision? A User Study, Baseline, And Dataset. Leon Sixt, Martin Schuessler, Oana-Iuliana Popescu, Philipp Weiß, Tim Landgraf |
| 2022 | Do We Need Anisotropic Graph Neural Networks? Shyam A. Tailor, Felix L. Opolka, Pietro Liò, Nicholas Donald Lane |
| 2022 | Do deep networks transfer invariances across classes? Allan Zhou, Fahim Tajwar, Alexander Robey, Tom Knowles, George J. Pappas, Hamed Hassani, Chelsea Finn |
| 2022 | Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features. Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf |
| 2022 | Domain Adversarial Training: A Game Perspective. David Acuna, Marc T. Law, Guojun Zhang, Sanja Fidler |
| 2022 | Domino: Discovering Systematic Errors with Cross-Modal Embeddings. Sabri Eyuboglu, Maya Varma, Khaled Kamal Saab, Jean-Benoit Delbrouck, Christopher Lee-Messer, Jared Dunnmon, James Zou, Christopher Ré |
| 2022 | Doubly Adaptive Scaled Algorithm for Machine Learning Using Second-Order Information. Majid Jahani, Sergey Rusakov, Zheng Shi, Peter Richtárik, Michael W. Mahoney, Martin Takác |
| 2022 | DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals. Cédric Allain, Alexandre Gramfort, Thomas Moreau |
| 2022 | Dropout Q-Functions for Doubly Efficient Reinforcement Learning. Takuya Hiraoka, Takahisa Imagawa, Taisei Hashimoto, Takashi Onishi, Yoshimasa Tsuruoka |
| 2022 | Dual Lottery Ticket Hypothesis. Yue Bai, Huan Wang, Zhiqiang Tao, Kunpeng Li, Yun Fu |
| 2022 | Dynamic Token Normalization improves Vision Transformers. Wenqi Shao, Yixiao Ge, Zhaoyang Zhang, Xuyuan Xu, Xiaogang Wang, Ying Shan, Ping Luo |
| 2022 | Dynamics-Aware Comparison of Learned Reward Functions. Blake Wulfe, Logan Michael Ellis, Jean Mercat, Rowan Thomas McAllister, Adrien Gaidon |
| 2022 | EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits. Yikun Ban, Yuchen Yan, Arindam Banerjee, Jingrui He |
| 2022 | EViT: Expediting Vision Transformers via Token Reorganizations. Youwei Liang, Chongjian Ge, Zhan Tong, Yibing Song, Jue Wang, Pengtao Xie |
| 2022 | EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression. Zirui Liu, Kaixiong Zhou, Fan Yang, Li Li, Rui Chen, Xia Hu |
| 2022 | Effect of scale on catastrophic forgetting in neural networks. Vinay Venkatesh Ramasesh, Aitor Lewkowycz, Ethan Dyer |
| 2022 | Effective Model Sparsification by Scheduled Grow-and-Prune Methods. Xiaolong Ma, Minghai Qin, Fei Sun, Zejiang Hou, Kun Yuan, Yi Xu, Yanzhi Wang, Yen-Kuang Chen, Rong Jin, Yuan Xie |
| 2022 | Efficient Active Search for Combinatorial Optimization Problems. André Hottung, Yeong-Dae Kwon, Kevin Tierney |
| 2022 | Efficient Computation of Deep Nonlinear Infinite-Width Neural Networks that Learn Features. Greg Yang, Michael Santacroce, Edward J. Hu |
| 2022 | Efficient Learning of Safe Driving Policy via Human-AI Copilot Optimization. Quanyi Li, Zhenghao Peng, Bolei Zhou |
| 2022 | Efficient Neural Causal Discovery without Acyclicity Constraints. Phillip Lippe, Taco Cohen, Efstratios Gavves |
| 2022 | Efficient Self-supervised Vision Transformers for Representation Learning. Chunyuan Li, Jianwei Yang, Pengchuan Zhang, Mei Gao, Bin Xiao, Xiyang Dai, Lu Yuan, Jianfeng Gao |
| 2022 | Efficient Sharpness-aware Minimization for Improved Training of Neural Networks. Jiawei Du, Hanshu Yan, Jiashi Feng, Joey Tianyi Zhou, Liangli Zhen, Rick Siow Mong Goh, Vincent Y. F. Tan |
| 2022 | Efficient Split-Mix Federated Learning for On-Demand and In-Situ Customization. Junyuan Hong, Haotao Wang, Zhangyang Wang, Jiayu Zhou |
| 2022 | Efficient Token Mixing for Transformers via Adaptive Fourier Neural Operators. John Guibas, Morteza Mardani, Zongyi Li, Andrew Tao, Anima Anandkumar, Bryan Catanzaro |
| 2022 | Efficient and Differentiable Conformal Prediction with General Function Classes. Yu Bai, Song Mei, Huan Wang, Yingbo Zhou, Caiming Xiong |
| 2022 | Efficiently Modeling Long Sequences with Structured State Spaces. Albert Gu, Karan Goel, Christopher Ré |
| 2022 | EigenGame Unloaded: When playing games is better than optimizing. Ian Gemp, Brian McWilliams, Claire Vernade, Thore Graepel |
| 2022 | Eigencurve: Optimal Learning Rate Schedule for SGD on Quadratic Objectives with Skewed Hessian Spectrums. Rui Pan, Haishan Ye, Tong Zhang |
| 2022 | Einops: Clear and Reliable Tensor Manipulations with Einstein-like Notation. Alex Rogozhnikov |
| 2022 | Eliminating Sharp Minima from SGD with Truncated Heavy-tailed Noise. Xingyu Wang, Sewoong Oh, Chang-Han Rhee |
| 2022 | Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling. Gianluigi Silvestri, Emily Fertig, Dave Moore, Luca Ambrogioni |
| 2022 | Emergent Communication at Scale. Rahma Chaabouni, Florian Strub, Florent Altché, Eugene Tarassov, Corentin Tallec, Elnaz Davoodi, Kory Wallace Mathewson, Olivier Tieleman, Angeliki Lazaridou, Bilal Piot |
| 2022 | Enabling Arbitrary Translation Objectives with Adaptive Tree Search. Wang Ling, Wojciech Stokowiec, Domenic Donato, Chris Dyer, Lei Yu, Laurent Sartran, Austin Matthews |
| 2022 | Encoding Weights of Irregular Sparsity for Fixed-to-Fixed Model Compression. Baeseong Park, Se Jung Kwon, Daehwan Oh, Byeongwook Kim, Dongsoo Lee |
| 2022 | End-to-End Learning of Probabilistic Hierarchies on Graphs. Daniel Zügner, Bertrand Charpentier, Morgane Ayle, Sascha Geringer, Stephan Günnemann |
| 2022 | Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning. Yatao Bian, Yu Rong, Tingyang Xu, Jiaxiang Wu, Andreas Krause, Junzhou Huang |
| 2022 | Energy-Inspired Molecular Conformation Optimization. Jiaqi Guan, Wesley Wei Qian, Qiang Liu, Wei-Ying Ma, Jianzhu Ma, Jian Peng |
| 2022 | Enhancing Cross-lingual Transfer by Manifold Mixup. Huiyun Yang, Huadong Chen, Hao Zhou, Lei Li |
| 2022 | EntQA: Entity Linking as Question Answering. Wenzheng Zhang, Wenyue Hua, Karl Stratos |
| 2022 | Entroformer: A Transformer-based Entropy Model for Learned Image Compression. Yichen Qian, Xiuyu Sun, Ming Lin, Zhiyu Tan, Rong Jin |
| 2022 | Environment Predictive Coding for Visual Navigation. Santhosh Kumar Ramakrishnan, Tushar Nagarajan, Ziad Al-Halah, Kristen Grauman |
| 2022 | Equivariant Graph Mechanics Networks with Constraints. Wenbing Huang, Jiaqi Han, Yu Rong, Tingyang Xu, Fuchun Sun, Junzhou Huang |
| 2022 | Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations. Rumen Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic |
| 2022 | Equivariant Subgraph Aggregation Networks. Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron |
| 2022 | Equivariant Transformers for Neural Network based Molecular Potentials. Philipp Thölke, Gianni De Fabritiis |
| 2022 | Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks. Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li |
| 2022 | Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems. Thomas Pethick, Puya Latafat, Panos Patrinos, Olivier Fercoq, Volkan Cevher |
| 2022 | Evading Adversarial Example Detection Defenses with Orthogonal Projected Gradient Descent. Oliver Bryniarski, Nabeel Hingun, Pedro Pachuca, Vincent Wang, Nicholas Carlini |
| 2022 | Evaluating Disentanglement of Structured Representations. Raphaël Dang-Nhu |
| 2022 | Evaluating Distributional Distortion in Neural Language Modeling. Benjamin LeBrun, Alessandro Sordoni, Timothy J. O'Donnell |
| 2022 | Evaluating Model-Based Planning and Planner Amortization for Continuous Control. Arunkumar Byravan, Leonard Hasenclever, Piotr Trochim, Mehdi Mirza, Alessandro Davide Ialongo, Yuval Tassa, Jost Tobias Springenberg, Abbas Abdolmaleki, Nicolas Heess, Josh Merel, Martin A. Riedmiller |
| 2022 | Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions. Leslie O'Bray, Max Horn, Bastian Rieck, Karsten M. Borgwardt |
| 2022 | Evidential Turing Processes. Melih Kandemir, Abdullah Akgül, Manuel Haußmann, Gozde Unal |
| 2022 | Evolutionary Diversity Optimization with Clustering-based Selection for Reinforcement Learning. Yutong Wang, Ke Xue, Chao Qian |
| 2022 | ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning. Vamsi Aribandi, Yi Tay, Tal Schuster, Jinfeng Rao, Huaixiu Steven Zheng, Sanket Vaibhav Mehta, Honglei Zhuang, Vinh Q. Tran, Dara Bahri, Jianmo Ni, Jai Prakash Gupta, Kai Hui, Sebastian Ruder, Donald Metzler |
| 2022 | Explainable GNN-Based Models over Knowledge Graphs. David Jaime Tena Cucala, Bernardo Cuenca Grau, Egor V. Kostylev, Boris Motik |
| 2022 | Explaining Point Processes by Learning Interpretable Temporal Logic Rules. Shuang Li, Mingquan Feng, Lu Wang, Abdelmajid Essofi, Yufeng Cao, Junchi Yan, Le Song |
| 2022 | Explanations of Black-Box Models based on Directional Feature Interactions. Aria Masoomi, Davin Hill, Zhonghui Xu, Craig P. Hersh, Edwin K. Silverman, Peter J. Castaldi, Stratis Ioannidis, Jennifer G. Dy |
| 2022 | Exploiting Class Activation Value for Partial-Label Learning. Fei Zhang, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Tao Qin, Masashi Sugiyama |
| 2022 | Exploring Memorization in Adversarial Training. Yinpeng Dong, Ke Xu, Xiao Yang, Tianyu Pang, Zhijie Deng, Hang Su, Jun Zhu |
| 2022 | Exploring extreme parameter compression for pre-trained language models. Benyou Wang, Yuxin Ren, Lifeng Shang, Xin Jiang, Qun Liu |
| 2022 | Exploring the Limits of Large Scale Pre-training. Samira Abnar, Mostafa Dehghani, Behnam Neyshabur, Hanie Sedghi |
| 2022 | Exposing the Implicit Energy Networks behind Masked Language Models via Metropolis--Hastings. Kartik Goyal, Chris Dyer, Taylor Berg-Kirkpatrick |
| 2022 | Expressiveness and Approximation Properties of Graph Neural Networks. Floris Geerts, Juan L. Reutter |
| 2022 | Expressivity of Emergent Languages is a Trade-off between Contextual Complexity and Unpredictability. Shangmin Guo, Yi Ren, Kory Wallace Mathewson, Simon Kirby, Stefano V. Albrecht, Kenny Smith |
| 2022 | Extending the WILDS Benchmark for Unsupervised Adaptation. Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang |
| 2022 | F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization. Qing Jin, Jian Ren, Richard Zhuang, Sumant Hanumante, Zhengang Li, Zhiyu Chen, Yanzhi Wang, Kaiyuan Yang, Sergey Tulyakov |
| 2022 | FALCON: Fast Visual Concept Learning by Integrating Images, Linguistic descriptions, and Conceptual Relations. Lingjie Mei, Jiayuan Mao, Ziqi Wang, Chuang Gan, Joshua B. Tenenbaum |
| 2022 | FILIP: Fine-grained Interactive Language-Image Pre-Training. Lewei Yao, Runhui Huang, Lu Hou, Guansong Lu, Minzhe Niu, Hang Xu, Xiaodan Liang, Zhenguo Li, Xin Jiang, Chunjing Xu |
| 2022 | FILM: Following Instructions in Language with Modular Methods. So Yeon Min, Devendra Singh Chaplot, Pradeep Kumar Ravikumar, Yonatan Bisk, Ruslan Salakhutdinov |
| 2022 | FP-DETR: Detection Transformer Advanced by Fully Pre-training. Wen Wang, Yang Cao, Jing Zhang, Dacheng Tao |
| 2022 | Fair Normalizing Flows. Mislav Balunovic, Anian Ruoss, Martin T. Vechev |
| 2022 | FairCal: Fairness Calibration for Face Verification. Tiago Salvador, Stephanie Cairns, Vikram Voleti, Noah Marshall, Adam M. Oberman |
| 2022 | Fairness Guarantees under Demographic Shift. Stephen Giguere, Blossom Metevier, Bruno Castro da Silva, Yuriy Brun, Philip S. Thomas, Scott Niekum |
| 2022 | Fairness in Representation for Multilingual NLP: Insights from Controlled Experiments on Conditional Language Modeling. Ada Wan |
| 2022 | Fast AdvProp. Jieru Mei, Yucheng Han, Yutong Bai, Yixiao Zhang, Yingwei Li, Xianhang Li, Alan L. Yuille, Cihang Xie |
| 2022 | Fast Differentiable Matrix Square Root. Yue Song, Nicu Sebe, Wei Wang |
| 2022 | Fast Generic Interaction Detection for Model Interpretability and Compression. Tianjian Zhang, Feng Yin, Zhi-Quan Luo |
| 2022 | Fast Model Editing at Scale. Eric Mitchell, Charles Lin, Antoine Bosselut, Chelsea Finn, Christopher D. Manning |
| 2022 | Fast Regression for Structured Inputs. Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou |
| 2022 | Fast topological clustering with Wasserstein distance. Tananun Songdechakraiwut, Bryan M. Krause, Matthew I. Banks, Kirill V. Nourski, Barry D. Van Veen |
| 2022 | FastSHAP: Real-Time Shapley Value Estimation. Neil Jethani, Mukund Sudarshan, Ian Connick Covert, Su-In Lee, Rajesh Ranganath |
| 2022 | Feature Kernel Distillation. Bobby He, Mete Ozay |
| 2022 | FedBABU: Toward Enhanced Representation for Federated Image Classification. Jaehoon Oh, Sangmook Kim, Se-Young Yun |
| 2022 | FedChain: Chained Algorithms for Near-optimal Communication Cost in Federated Learning. Charlie Hou, Kiran Koshy Thekumparampil, Giulia Fanti, Sewoong Oh |
| 2022 | FedPara: Low-rank Hadamard Product for Communication-Efficient Federated Learning. Nam Hyeon-Woo, Moon Ye-Bin, Tae-Hyun Oh |
| 2022 | Federated Learning from Only Unlabeled Data with Class-conditional-sharing Clients. Nan Lu, Zhao Wang, Xiaoxiao Li, Gang Niu, Qi Dou, Masashi Sugiyama |
| 2022 | Few-Shot Backdoor Attacks on Visual Object Tracking. Yiming Li, Haoxiang Zhong, Xingjun Ma, Yong Jiang, Shu-Tao Xia |
| 2022 | Few-shot Learning via Dirichlet Tessellation Ensemble. Chunwei Ma, Ziyun Huang, Mingchen Gao, Jinhui Xu |
| 2022 | Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks. Andrea Cini, Ivan Marisca, Cesare Alippi |
| 2022 | Filtered-CoPhy: Unsupervised Learning of Counterfactual Physics in Pixel Space. Steeven Janny, Fabien Baradel, Natalia Neverova, Madiha Nadri, Greg Mori, Christian Wolf |
| 2022 | Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks. Anne Harrington, Arturo Deza |
| 2022 | Finding an Unsupervised Image Segmenter in each of your Deep Generative Models. Luke Melas-Kyriazi, Christian Rupprecht, Iro Laina, Andrea Vedaldi |
| 2022 | Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution. Ananya Kumar, Aditi Raghunathan, Robbie Matthew Jones, Tengyu Ma, Percy Liang |
| 2022 | Fine-grained Differentiable Physics: A Yarn-level Model for Fabrics. Deshan Gong, Zhanxing Zhu, Andrew J. Bulpitt, He Wang |
| 2022 | Finetuned Language Models are Zero-Shot Learners. Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, Quoc V. Le |
| 2022 | Finite-Time Convergence and Sample Complexity of Multi-Agent Actor-Critic Reinforcement Learning with Average Reward. Hairi, Jia Liu, Songtao Lu |
| 2022 | Fixed Neural Network Steganography: Train the images, not the network. Varsha Kishore, Xiangyu Chen, Yan Wang, Boyi Li, Kilian Q. Weinberger |
| 2022 | FlexConv: Continuous Kernel Convolutions With Differentiable Kernel Sizes. David W. Romero, Robert-Jan Bruintjes, Jakub Mikolaj Tomczak, Erik J. Bekkers, Mark Hoogendoorn, Jan van Gemert |
| 2022 | Focus on the Common Good: Group Distributional Robustness Follows. Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi |
| 2022 | Fooling Explanations in Text Classifiers. Adam Ivankay, Ivan Girardi, Chiara Marchiori, Pascal Frossard |
| 2022 | Fortuitous Forgetting in Connectionist Networks. Hattie Zhou, Ankit Vani, Hugo Larochelle, Aaron C. Courville |
| 2022 | Frame Averaging for Invariant and Equivariant Network Design. Omri Puny, Matan Atzmon, Edward J. Smith, Ishan Misra, Aditya Grover, Heli Ben-Hamu, Yaron Lipman |
| 2022 | Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan |
| 2022 | From Intervention to Domain Transportation: A Novel Perspective to Optimize Recommendation. Da Xu, Yuting Ye, Chuanwei Ruan, Evren Körpeoglu, Sushant Kumar, Kannan Achan |
| 2022 | From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness. Lingxiao Zhao, Wei Jin, Leman Akoglu, Neil Shah |
| 2022 | GATSBI: Generative Adversarial Training for Simulation-Based Inference. Poornima Ramesh, Jan-Matthis Lueckmann, Jan Boelts, Álvaro Tejero-Cantero, David S. Greenberg, Pedro J. Gonçalves, Jakob H. Macke |
| 2022 | GDA-AM: On the Effectiveness of Solving Min-Imax Optimization via Anderson Mixing. Huan He, Shifan Zhao, Yuanzhe Xi, Joyce C. Ho, Yousef Saad |
| 2022 | GLASS: GNN with Labeling Tricks for Subgraph Representation Learning. Xiyuan Wang, Muhan Zhang |
| 2022 | GNN is a Counter? Revisiting GNN for Question Answering. Kuan Wang, Yuyu Zhang, Diyi Yang, Le Song, Tao Qin |
| 2022 | GNN-LM: Language Modeling based on Global Contexts via GNN. Yuxian Meng, Shi Zong, Xiaoya Li, Xiaofei Sun, Tianwei Zhang, Fei Wu, Jiwei Li |
| 2022 | GPT-Critic: Offline Reinforcement Learning for End-to-End Task-Oriented Dialogue Systems. Youngsoo Jang, Jongmin Lee, Kee-Eung Kim |
| 2022 | GRAND++: Graph Neural Diffusion with A Source Term. Matthew Thorpe, Tan Minh Nguyen, Hedi Xia, Thomas Strohmer, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang |
| 2022 | Gaussian Mixture Convolution Networks. Adam Celarek, Pedro Hermosilla, Bernhard Kerbl, Timo Ropinski, Michael Wimmer |
| 2022 | GeneDisco: A Benchmark for Experimental Design in Drug Discovery. Arash Mehrjou, Ashkan Soleymani, Andrew Jesson, Pascal Notin, Yarin Gal, Stefan Bauer, Patrick Schwab |
| 2022 | Generalisation in Lifelong Reinforcement Learning through Logical Composition. Geraud Nangue Tasse, Steven James, Benjamin Rosman |
| 2022 | Generalization Through the Lens of Leave-One-Out Error. Gregor Bachmann, Thomas Hofmann, Aurélien Lucchi |
| 2022 | Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness. Simon Geisler, Johanna Sommer, Jan Schuchardt, Aleksandar Bojchevski, Stephan Günnemann |
| 2022 | Generalized Decision Transformer for Offline Hindsight Information Matching. Hiroki Furuta, Yutaka Matsuo, Shixiang Shane Gu |
| 2022 | Generalized Demographic Parity for Group Fairness. Zhimeng Jiang, Xiaotian Han, Chao Fan, Fan Yang, Ali Mostafavi, Xia Hu |
| 2022 | Generalized Kernel Thinning. Raaz Dwivedi, Lester Mackey |
| 2022 | Generalized Natural Gradient Flows in Hidden Convex-Concave Games and GANs. Andjela Mladenovic, Iosif Sakos, Gauthier Gidel, Georgios Piliouras |
| 2022 | Generalized rectifier wavelet covariance models for texture synthesis. Antoine Brochard, Sixin Zhang, Stéphane Mallat |
| 2022 | Generalizing Few-Shot NAS with Gradient Matching. Shoukang Hu, Ruochen Wang, Lanqing Hong, Zhenguo Li, Cho-Jui Hsieh, Jiashi Feng |
| 2022 | Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks. Sihyun Yu, Jihoon Tack, Sangwoo Mo, Hyunsu Kim, Junho Kim, Jung-Woo Ha, Jinwoo Shin |
| 2022 | Generative Modeling with Optimal Transport Maps. Litu Rout, Alexander Korotin, Evgeny Burnaev |
| 2022 | Generative Models as a Data Source for Multiview Representation Learning. Ali Jahanian, Xavier Puig, Yonglong Tian, Phillip Isola |
| 2022 | Generative Planning for Temporally Coordinated Exploration in Reinforcement Learning. Haichao Zhang, Wei Xu, Haonan Yu |
| 2022 | Generative Principal Component Analysis. Zhaoqiang Liu, Jiulong Liu, Subhroshekhar Ghosh, Jun Han, Jonathan Scarlett |
| 2022 | Generative Pseudo-Inverse Memory. Kha Pham, Hung Le, Man Ngo, Truyen Tran, Bao Ho, Svetha Venkatesh |
| 2022 | GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation. Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang |
| 2022 | Geometric Transformers for Protein Interface Contact Prediction. Alex Morehead, Chen Chen, Jianlin Cheng |
| 2022 | Geometric and Physical Quantities improve E(3) Equivariant Message Passing. Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J. Bekkers, Max Welling |
| 2022 | Geometry-Consistent Neural Shape Representation with Implicit Displacement Fields. Yifan Wang, Lukas Rahmann, Olga Sorkine-Hornung |
| 2022 | GiraffeDet: A Heavy-Neck Paradigm for Object Detection. Yiqi Jiang, Zhiyu Tan, Junyan Wang, Xiuyu Sun, Ming Lin, Hao Li |
| 2022 | Givens Coordinate Descent Methods for Rotation Matrix Learning in Trainable Embedding Indexes. Yunjiang Jiang, Han Zhang, Yiming Qiu, Yun Xiao, Bo Long, Wen-Yun Yang |
| 2022 | Global Convergence of Multi-Agent Policy Gradient in Markov Potential Games. Stefanos Leonardos, Will Overman, Ioannis Panageas, Georgios Piliouras |
| 2022 | Goal-Directed Planning via Hindsight Experience Replay. Lorenzo Moro, Amarildo Likmeta, Enrico Prati, Marcello Restelli |
| 2022 | GradMax: Growing Neural Networks using Gradient Information. Utku Evci, Bart van Merrienboer, Thomas Unterthiner, Fabian Pedregosa, Max Vladymyrov |
| 2022 | GradSign: Model Performance Inference with Theoretical Insights. Zhihao Zhang, Zhihao Jia |
| 2022 | Gradient Importance Learning for Incomplete Observations. Qitong Gao, Dong Wang, Joshua David Amason, Siyang Yuan, Chenyang Tao, Ricardo Henao, Majda Hadziahmetovic, Lawrence Carin, Miroslav Pajic |
| 2022 | Gradient Information Matters in Policy Optimization by Back-propagating through Model. Chongchong Li, Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu |
| 2022 | Gradient Matching for Domain Generalization. Yuge Shi, Jeffrey Seely, Philip H. S. Torr, Siddharth Narayanaswamy, Awni Y. Hannun, Nicolas Usunier, Gabriel Synnaeve |
| 2022 | Gradient Step Denoiser for convergent Plug-and-Play. Samuel Hurault, Arthur Leclaire, Nicolas Papadakis |
| 2022 | Granger causal inference on DAGs identifies genomic loci regulating transcription. Alexander P. Wu, Rohit Singh, Bonnie Berger |
| 2022 | Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction. Mingyue Tang, Pan Li, Carl Yang |
| 2022 | Graph Condensation for Graph Neural Networks. Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah |
| 2022 | Graph Neural Network Guided Local Search for the Traveling Salesperson Problem. Benjamin Hudson, Qingbiao Li, Matthew Malencia, Amanda Prorok |
| 2022 | Graph Neural Networks with Learnable Structural and Positional Representations. Vijay Prakash Dwivedi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, Xavier Bresson |
| 2022 | Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series. Enyan Dai, Jie Chen |
| 2022 | Graph-Guided Network for Irregularly Sampled Multivariate Time Series. Xiang Zhang, Marko Zeman, Theodoros Tsiligkaridis, Marinka Zitnik |
| 2022 | Graph-Relational Domain Adaptation. Zihao Xu, Hao He, Guang-He Lee, Bernie Wang, Hao Wang |
| 2022 | Graph-based Nearest Neighbor Search in Hyperbolic Spaces. Liudmila Prokhorenkova, Dmitry Baranchuk, Nikolay Bogachev, Yury Demidovich, Alexander Kolpakov |
| 2022 | Graph-less Neural Networks: Teaching Old MLPs New Tricks Via Distillation. Shichang Zhang, Yozen Liu, Yizhou Sun, Neil Shah |
| 2022 | GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification. Joonhyung Park, Jaeyun Song, Eunho Yang |
| 2022 | Graphon based Clustering and Testing of Networks: Algorithms and Theory. Mahalakshmi Sabanayagam, Leena Chennuru Vankadara, Debarghya Ghoshdastidar |
| 2022 | GreaseLM: Graph REASoning Enhanced Language Models. Xikun Zhang, Antoine Bosselut, Michihiro Yasunaga, Hongyu Ren, Percy Liang, Christopher D. Manning, Jure Leskovec |
| 2022 | Group equivariant neural posterior estimation. Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Deistler, Bernhard Schölkopf, Jakob H. Macke |
| 2022 | Group-based Interleaved Pipeline Parallelism for Large-scale DNN Training. Pengcheng Yang, Xiaoming Zhang, Wenpeng Zhang, Ming Yang, Hong Wei |
| 2022 | HTLM: Hyper-Text Pre-Training and Prompting of Language Models. Armen Aghajanyan, Dmytro Okhonko, Mike Lewis, Mandar Joshi, Hu Xu, Gargi Ghosh, Luke Zettlemoyer |
| 2022 | Half-Inverse Gradients for Physical Deep Learning. Patrick Schnell, Philipp Holl, Nils Thuerey |
| 2022 | Handling Distribution Shifts on Graphs: An Invariance Perspective. Qitian Wu, Hengrui Zhang, Junchi Yan, David Wipf |
| 2022 | Heteroscedastic Temporal Variational Autoencoder For Irregularly Sampled Time Series. Satya Narayan Shukla, Benjamin M. Marlin |
| 2022 | Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions. Arda Sahiner, Tolga Ergen, Batu Ozturkler, Burak Bartan, John M. Pauly, Morteza Mardani, Mert Pilanci |
| 2022 | Hidden Parameter Recurrent State Space Models For Changing Dynamics Scenarios. Vaisakh Shaj, Dieter Büchler, Rohit Sonker, Philipp Becker, Gerhard Neumann |
| 2022 | Hierarchical Few-Shot Imitation with Skill Transition Models. Kourosh Hakhamaneshi, Ruihan Zhao, Albert Zhan, Pieter Abbeel, Michael Laskin |
| 2022 | Hierarchical Variational Memory for Few-shot Learning Across Domains. Ying-Jun Du, Xiantong Zhen, Ling Shao, Cees G. M. Snoek |
| 2022 | High Probability Bounds for a Class of Nonconvex Algorithms with AdaGrad Stepsize. Ali Kavis, Kfir Yehuda Levy, Volkan Cevher |
| 2022 | High Probability Generalization Bounds with Fast Rates for Minimax Problems. Shaojie Li, Yong Liu |
| 2022 | Hindsight Foresight Relabeling for Meta-Reinforcement Learning. Michael Wan, Jian Peng, Tanmay Gangwani |
| 2022 | Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception. Yurong You, Katie Z. Luo, Xiangyu Chen, Junan Chen, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger |
| 2022 | Hindsight: Posterior-guided training of retrievers for improved open-ended generation. Ashwin Paranjape, Omar Khattab, Christopher Potts, Matei Zaharia, Christopher D. Manning |
| 2022 | Hot-Refresh Model Upgrades with Regression-Free Compatible Training in Image Retrieval. Binjie Zhang, Yixiao Ge, Yantao Shen, Yu Li, Chun Yuan, Xuyuan Xu, Yexin Wang, Ying Shan |
| 2022 | How Attentive are Graph Attention Networks? Shaked Brody, Uri Alon, Eran Yahav |
| 2022 | How Did the Model Change? Efficiently Assessing Machine Learning API Shifts. Lingjiao Chen, Matei Zaharia, James Zou |
| 2022 | How Do Vision Transformers Work? Namuk Park, Songkuk Kim |
| 2022 | How Does SimSiam Avoid Collapse Without Negative Samples? A Unified Understanding with Self-supervised Contrastive Learning. Chaoning Zhang, Kang Zhang, Chenshuang Zhang, Trung X. Pham, Chang D. Yoo, In So Kweon |
| 2022 | How Low Can We Go: Trading Memory for Error in Low-Precision Training. Chengrun Yang, Ziyang Wu, Jerry Chee, Christopher De Sa, Madeleine Udell |
| 2022 | How Much Can CLIP Benefit Vision-and-Language Tasks? Sheng Shen, Liunian Harold Li, Hao Tan, Mohit Bansal, Anna Rohrbach, Kai-Wei Chang, Zhewei Yao, Kurt Keutzer |
| 2022 | How Well Does Self-Supervised Pre-Training Perform with Streaming Data? Dapeng Hu, Shipeng Yan, Qizhengqiu Lu, Lanqing Hong, Hailin Hu, Yifan Zhang, Zhenguo Li, Xinchao Wang, Jiashi Feng |
| 2022 | How many degrees of freedom do we need to train deep networks: a loss landscape perspective. Brett W. Larsen, Stanislav Fort, Nic Becker, Surya Ganguli |
| 2022 | How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data. Zhiyuan Zhang, Lingjuan Lyu, Weiqiang Wang, Lichao Sun, Xu Sun |
| 2022 | How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective. Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jinfeng Yi, Mingyi Hong, Shiyu Chang, Sijia Liu |
| 2022 | How to Train Your MAML to Excel in Few-Shot Classification. Han-Jia Ye, Wei-Lun Chao |
| 2022 | How to deal with missing data in supervised deep learning? Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen |
| 2022 | How unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis. Shuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong |
| 2022 | Huber Additive Models for Non-stationary Time Series Analysis. Yingjie Wang, Xianrui Zhong, Fengxiang He, Hong Chen, Dacheng Tao |
| 2022 | HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation. Boyan Li, Hongyao Tang, Yan Zheng, Jianye Hao, Pengyi Li, Zhen Wang, Zhaopeng Meng, Li Wang |
| 2022 | Hybrid Local SGD for Federated Learning with Heterogeneous Communications. Yuanxiong Guo, Ying Sun, Rui Hu, Yanmin Gong |
| 2022 | Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface. Tuan Anh Le, Katherine M. Collins, Luke Hewitt, Kevin Ellis, Siddharth Narayanaswamy, Samuel Gershman, Joshua B. Tenenbaum |
| 2022 | Hybrid Random Features. Krzysztof Marcin Choromanski, Han Lin, Haoxian Chen, Arijit Sehanobish, Yuanzhe Ma, Deepali Jain, Jake Varley, Andy Zeng, Michael S. Ryoo, Valerii Likhosherstov, Dmitry Kalashnikov, Vikas Sindhwani, Adrian Weller |
| 2022 | HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning. Ziniu Li, Yingru Li, Yushun Zhang, Tong Zhang, Zhi-Quan Luo |
| 2022 | Hyperparameter Tuning with Renyi Differential Privacy. Nicolas Papernot, Thomas Steinke |
| 2022 | IFR-Explore: Learning Inter-object Functional Relationships in 3D Indoor Scenes. Qi Li, Kaichun Mo, Yanchao Yang, Hang Zhao, Leonidas J. Guibas |
| 2022 | IGLU: Efficient GCN Training via Lazy Updates. S. Deepak Narayanan, Aditya Sinha, Prateek Jain, Purushottam Kar, Sundararajan Sellamanickam |
| 2022 | Igeood: An Information Geometry Approach to Out-of-Distribution Detection. Eduardo Dadalto Câmara Gomes, Florence Alberge, Pierre Duhamel, Pablo Piantanida |
| 2022 | Illiterate DALL-E Learns to Compose. Gautam Singh, Fei Deng, Sungjin Ahn |
| 2022 | Image BERT Pre-training with Online Tokenizer. Jinghao Zhou, Chen Wei, Huiyu Wang, Wei Shen, Cihang Xie, Alan L. Yuille, Tao Kong |
| 2022 | Imbedding Deep Neural Networks. Andrew Corbett, Dmitry Kangin |
| 2022 | Imitation Learning by Reinforcement Learning. Kamil Ciosek |
| 2022 | Imitation Learning from Observations under Transition Model Disparity. Tanmay Gangwani, Yuan Zhou, Jian Peng |
| 2022 | Implicit Bias of Adversarial Training for Deep Neural Networks. Bochen Lv, Zhanxing Zhu |
| 2022 | Implicit Bias of MSE Gradient Optimization in Underparameterized Neural Networks. Benjamin Bowman, Guido Montúfar |
| 2022 | Implicit Bias of Projected Subgradient Method Gives Provable Robust Recovery of Subspaces of Unknown Codimension. Paris Giampouras, Benjamin David Haeffele, René Vidal |
| 2022 | Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100. Sahil Singla, Surbhi Singla, Soheil Feizi |
| 2022 | Improving Federated Learning Face Recognition via Privacy-Agnostic Clusters. Qiang Meng, Feng Zhou, Hainan Ren, Tianshu Feng, Guochao Liu, Yuanqing Lin |
| 2022 | Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger Baker Grosse, Alireza Makhzani |
| 2022 | Improving Non-Autoregressive Translation Models Without Distillation. Xiao Shi Huang, Felipe Pérez, Maksims Volkovs |
| 2022 | Improving the Accuracy of Learning Example Weights for Imbalance Classification. Yuqi Liu, Bin Cao, Jing Fan |
| 2022 | In a Nutshell, the Human Asked for This: Latent Goals for Following Temporal Specifications. Borja G. León, Murray Shanahan, Francesco Belardinelli |
| 2022 | Increasing the Cost of Model Extraction with Calibrated Proof of Work. Adam Dziedzic, Muhammad Ahmad Kaleem, Yu Shen Lu, Nicolas Papernot |
| 2022 | Incremental False Negative Detection for Contrastive Learning. Tsai-Shien Chen, Wei-Chih Hung, Hung-Yu Tseng, Shao-Yi Chien, Ming-Hsuan Yang |
| 2022 | Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking. Octavian-Eugen Ganea, Xinyuan Huang, Charlotte Bunne, Yatao Bian, Regina Barzilay, Tommi S. Jaakkola, Andreas Krause |
| 2022 | Inductive Relation Prediction Using Analogy Subgraph Embeddings. Jiarui Jin, Yangkun Wang, Kounianhua Du, Weinan Zhang, Zheng Zhang, David Wipf, Yong Yu, Quan Gan |
| 2022 | InfinityGAN: Towards Infinite-Pixel Image Synthesis. Chieh Hubert Lin, Hsin-Ying Lee, Yen-Chi Cheng, Sergey Tulyakov, Ming-Hsuan Yang |
| 2022 | Information Bottleneck: Exact Analysis of (Quantized) Neural Networks. Stephan Sloth Lorenzen, Christian Igel, Mads Nielsen |
| 2022 | Information Gain Propagation: a New Way to Graph Active Learning with Soft Labels. Wentao Zhang, Yexin Wang, Zhenbang You, Meng Cao, Ping Huang, Jiulong Shan, Zhi Yang, Bin Cui |
| 2022 | Information Prioritization through Empowerment in Visual Model-based RL. Homanga Bharadhwaj, Mohammad Babaeizadeh, Dumitru Erhan, Sergey Levine |
| 2022 | Information-theoretic Online Memory Selection for Continual Learning. Shengyang Sun, Daniele Calandriello, Huiyi Hu, Ang Li, Michalis K. Titsias |
| 2022 | IntSGD: Adaptive Floatless Compression of Stochastic Gradients. Konstantin Mishchenko, Bokun Wang, Dmitry Kovalev, Peter Richtárik |
| 2022 | Interacting Contour Stochastic Gradient Langevin Dynamics. Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang |
| 2022 | Interpretable Unsupervised Diversity Denoising and Artefact Removal. Mangal Prakash, Mauricio Delbracio, Peyman Milanfar, Florian Jug |
| 2022 | Invariant Causal Representation Learning for Out-of-Distribution Generalization. Chaochao Lu, Yuhuai Wu, José Miguel Hernández-Lobato, Bernhard Schölkopf |
| 2022 | Inverse Online Learning: Understanding Non-Stationary and Reactionary Policies. Alex J. Chan, Alicia Curth, Mihaela van der Schaar |
| 2022 | Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning. Natalie Dullerud, Karsten Roth, Kimia Hamidieh, Nicolas Papernot, Marzyeh Ghassemi |
| 2022 | Is High Variance Unavoidable in RL? A Case Study in Continuous Control. Johan Bjorck, Carla P. Gomes, Kilian Q. Weinberger |
| 2022 | Is Homophily a Necessity for Graph Neural Networks? Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang |
| 2022 | Is Importance Weighting Incompatible with Interpolating Classifiers? Ke Alexander Wang, Niladri Shekhar Chatterji, Saminul Haque, Tatsunori Hashimoto |
| 2022 | It Takes Four to Tango: Multiagent Self Play for Automatic Curriculum Generation. Yuqing Du, Pieter Abbeel, Aditya Grover |
| 2022 | It Takes Two to Tango: Mixup for Deep Metric Learning. Shashanka Venkataramanan, Bill Psomas, Ewa Kijak, Laurent Amsaleg, Konstantinos Karantzalos, Yannis Avrithis |
| 2022 | Iterated Reasoning with Mutual Information in Cooperative and Byzantine Decentralized Teaming. Sachin G. Konan, Esmaeil Seraj, Matthew C. Gombolay |
| 2022 | Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design. Wengong Jin, Jeremy Wohlwend, Regina Barzilay, Tommi S. Jaakkola |
| 2022 | Joint Shapley values: a measure of joint feature importance. Chris Harris, Richard Pymar, Colin Rowat |
| 2022 | KL Guided Domain Adaptation. A. Tuan Nguyen, Toan Tran, Yarin Gal, Philip H. S. Torr, Atilim Gunes Baydin |
| 2022 | Know Thyself: Transferable Visual Control Policies Through Robot-Awareness. Edward S. Hu, Kun Huang, Oleh Rybkin, Dinesh Jayaraman |
| 2022 | Know Your Action Set: Learning Action Relations for Reinforcement Learning. Ayush Jain, Norio Kosaka, Kyung-Min Kim, Joseph J. Lim |
| 2022 | Knowledge Infused Decoding. Ruibo Liu, Guoqing Zheng, Shashank Gupta, Radhika Gaonkar, Chongyang Gao, Soroush Vosoughi, Milad Shokouhi, Ahmed Hassan Awadallah |
| 2022 | Knowledge Removal in Sampling-based Bayesian Inference. Shaopeng Fu, Fengxiang He, Dacheng Tao |
| 2022 | L0-Sparse Canonical Correlation Analysis. Ofir Lindenbaum, Moshe Salhov, Amir Averbuch, Yuval Kluger |
| 2022 | LFPT5: A Unified Framework for Lifelong Few-shot Language Learning Based on Prompt Tuning of T5. Chengwei Qin, Shafiq R. Joty |
| 2022 | LIGS: Learnable Intrinsic-Reward Generation Selection for Multi-Agent Learning. David Henry Mguni, Taher Jafferjee, Jianhong Wang, Nicolas Perez Nieves, Oliver Slumbers, Feifei Tong, Yang Li, Jiangcheng Zhu, Yaodong Yang, Jun Wang |
| 2022 | LORD: Lower-Dimensional Embedding of Log-Signature in Neural Rough Differential Equations. Jaehoon Lee, Jinsung Jeon, Sheo Yon Jhin, Jihyeon Hyeong, Jayoung Kim, Minju Jo, Seungji Kook, Noseong Park |
| 2022 | Label Encoding for Regression Networks. Deval Shah, Zi Yu Xue, Tor M. Aamodt |
| 2022 | Label Leakage and Protection in Two-party Split Learning. Oscar Li, Jiankai Sun, Xin Yang, Weihao Gao, Hongyi Zhang, Junyuan Xie, Virginia Smith, Chong Wang |
| 2022 | Label-Efficient Semantic Segmentation with Diffusion Models. Dmitry Baranchuk, Andrey Voynov, Ivan Rubachev, Valentin Khrulkov, Artem Babenko |
| 2022 | Language model compression with weighted low-rank factorization. Yen-Chang Hsu, Ting Hua, Sungen Chang, Qian Lou, Yilin Shen, Hongxia Jin |
| 2022 | Language modeling via stochastic processes. Rose E. Wang, Esin Durmus, Noah D. Goodman, Tatsunori Hashimoto |
| 2022 | Language-biased image classification: evaluation based on semantic representations. Yoann Lemesle, Masataka Sawayama, Guillermo Valle Pérez, Maxime Adolphe, Hélène Sauzéon, Pierre-Yves Oudeyer |
| 2022 | Language-driven Semantic Segmentation. Boyi Li, Kilian Q. Weinberger, Serge J. Belongie, Vladlen Koltun, René Ranftl |
| 2022 | Large Language Models Can Be Strong Differentially Private Learners. Xuechen Li, Florian Tramèr, Percy Liang, Tatsunori Hashimoto |
| 2022 | Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect. Yuqing Wang, Minshuo Chen, Tuo Zhao, Molei Tao |
| 2022 | Large-Scale Representation Learning on Graphs via Bootstrapping. Shantanu Thakoor, Corentin Tallec, Mohammad Gheshlaghi Azar, Mehdi Azabou, Eva L. Dyer, Rémi Munos, Petar Velickovic, Michal Valko |
| 2022 | Latent Image Animator: Learning to Animate Images via Latent Space Navigation. Yaohui Wang, Di Yang, François Brémond, Antitza Dantcheva |
| 2022 | Latent Variable Sequential Set Transformers for Joint Multi-Agent Motion Prediction. Roger Girgis, Florian Golemo, Felipe Codevilla, Martin Weiss, Jim Aldon D'Souza, Samira Ebrahimi Kahou, Felix Heide, Christopher Pal |
| 2022 | Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks. Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Mahmut T. Kandemir, Anand Sivasubramaniam |
| 2022 | Learnability Lock: Authorized Learnability Control Through Adversarial Invertible Transformations. Weiqi Peng, Jinghui Chen |
| 2022 | Learnability of convolutional neural networks for infinite dimensional input via mixed and anisotropic smoothness. Sho Okumoto, Taiji Suzuki |
| 2022 | Learned Simulators for Turbulence. Kimberly L. Stachenfeld, Drummond Buschman Fielding, Dmitrii Kochkov, Miles D. Cranmer, Tobias Pfaff, Jonathan Godwin, Can Cui, Shirley Ho, Peter W. Battaglia, Alvaro Sanchez-Gonzalez |
| 2022 | Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations. Keir Adams, Lagnajit Pattanaik, Connor W. Coley |
| 2022 | Learning Altruistic Behaviours in Reinforcement Learning without External Rewards. Tim Franzmeyer, Mateusz Malinowski, João F. Henriques |
| 2022 | Learning Audio-Visual Speech Representation by Masked Multimodal Cluster Prediction. Bowen Shi, Wei-Ning Hsu, Kushal Lakhotia, Abdelrahman Mohamed |
| 2022 | Learning Causal Models from Conditional Moment Restrictions by Importance Weighting. Masahiro Kato, Masaaki Imaizumi, Kenichiro McAlinn, Shota Yasui, Haruo Kakehi |
| 2022 | Learning Continuous Environment Fields via Implicit Functions. Xueting Li, Shalini De Mello, Xiaolong Wang, Ming-Hsuan Yang, Jan Kautz, Sifei Liu |
| 2022 | Learning Curves for Gaussian Process Regression with Power-Law Priors and Targets. Hui Jin, Pradeep Kr. Banerjee, Guido Montúfar |
| 2022 | Learning Curves for SGD on Structured Features. Blake Bordelon, Cengiz Pehlevan |
| 2022 | Learning Discrete Structured Variational Auto-Encoder using Natural Evolution Strategies. Alon Berliner, Guy Rotman, Yossi Adi, Roi Reichart, Tamir Hazan |
| 2022 | Learning Disentangled Representation by Exploiting Pretrained Generative Models: A Contrastive Learning View. Xuanchi Ren, Tao Yang, Yuwang Wang, Wenjun Zeng |
| 2022 | Learning Distributionally Robust Models at Scale via Composite Optimization. Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Amin Karbasi |
| 2022 | Learning Efficient Image Super-Resolution Networks via Structure-Regularized Pruning. Yulun Zhang, Huan Wang, Can Qin, Yun Fu |
| 2022 | Learning Efficient Online 3D Bin Packing on Packing Configuration Trees. Hang Zhao, Yang Yu, Kai Xu |
| 2022 | Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality. Daniel Watson, William Chan, Jonathan Ho, Mohammad Norouzi |
| 2022 | Learning Fast, Learning Slow: A General Continual Learning Method based on Complementary Learning System. Elahe Arani, Fahad Sarfraz, Bahram Zonooz |
| 2022 | Learning Features with Parameter-Free Layers. Dongyoon Han, Young Joon Yoo, Beomyoung Kim, Byeongho Heo |
| 2022 | Learning Generalizable Representations for Reinforcement Learning via Adaptive Meta-learner of Behavioral Similarities. Jianda Chen, Sinno Jialin Pan |
| 2022 | Learning Graphon Mean Field Games and Approximate Nash Equilibria. Kai Cui, Heinz Koeppl |
| 2022 | Learning Guarantees for Graph Convolutional Networks on the Stochastic Block Model. Wei Lu |
| 2022 | Learning Hierarchical Structures with Differentiable Nondeterministic Stacks. Brian DuSell, David Chiang |
| 2022 | Learning Long-Term Reward Redistribution via Randomized Return Decomposition. Zhizhou Ren, Ruihan Guo, Yuan Zhou, Jian Peng |
| 2022 | Learning Multimodal VAEs through Mutual Supervision. Tom Joy, Yuge Shi, Philip H. S. Torr, Tom Rainforth, Sebastian M. Schmon, Siddharth Narayanaswamy |
| 2022 | Learning Neural Contextual Bandits through Perturbed Rewards. Yiling Jia, Weitong Zhang, Dongruo Zhou, Quanquan Gu, Hongning Wang |
| 2022 | Learning Object-Oriented Dynamics for Planning from Text. Guiliang Liu, Ashutosh Adhikari, Amir-massoud Farahmand, Pascal Poupart |
| 2022 | Learning Optimal Conformal Classifiers. David Stutz, Krishnamurthy Dvijotham, Ali Taylan Cemgil, Arnaud Doucet |
| 2022 | Learning Prototype-oriented Set Representations for Meta-Learning. Dandan Guo, Long Tian, Minghe Zhang, Mingyuan Zhou, Hongyuan Zha |
| 2022 | Learning Pruning-Friendly Networks via Frank-Wolfe: One-Shot, Any-Sparsity, And No Retraining. Lu Miao, Xiaolong Luo, Tianlong Chen, Wuyang Chen, Dong Liu, Zhangyang Wang |
| 2022 | Learning Representation from Neural Fisher Kernel with Low-rank Approximation. Ruixiang Zhang, Shuangfei Zhai, Etai Littwin, Joshua M. Susskind |
| 2022 | Learning Scenario Representation for Solving Two-stage Stochastic Integer Programs. Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang |
| 2022 | Learning State Representations via Retracing in Reinforcement Learning. Changmin Yu, Dong Li, Jianye Hao, Jun Wang, Neil Burgess |
| 2022 | Learning Strides in Convolutional Neural Networks. Rachid Riad, Olivier Teboul, David Grangier, Neil Zeghidour |
| 2022 | Learning Super-Features for Image Retrieval. Philippe Weinzaepfel, Thomas Lucas, Diane Larlus, Yannis Kalantidis |
| 2022 | Learning Synthetic Environments and Reward Networks for Reinforcement Learning. Fabio Ferreira, Thomas Nierhoff, Andreas Sälinger, Frank Hutter |
| 2022 | Learning Temporally Causal Latent Processes from General Temporal Data. Weiran Yao, Yuewen Sun, Alex Ho, Changyin Sun, Kun Zhang |
| 2022 | Learning Towards The Largest Margins. Xiong Zhou, Xianming Liu, Deming Zhai, Junjun Jiang, Xin Gao, Xiangyang Ji |
| 2022 | Learning Transferable Reward for Query Object Localization with Policy Adaptation. Tingfeng Li, Shaobo Han, Martin Renqiang Min, Dimitris N. Metaxas |
| 2022 | Learning Value Functions from Undirected State-only Experience. Matthew Chang, Arjun Gupta, Saurabh Gupta |
| 2022 | Learning Versatile Neural Architectures by Propagating Network Codes. Mingyu Ding, Yuqi Huo, Haoyu Lu, Linjie Yang, Zhe Wang, Zhiwu Lu, Jingdong Wang, Ping Luo |
| 2022 | Learning Vision-Guided Quadrupedal Locomotion End-to-End with Cross-Modal Transformers. Ruihan Yang, Minghao Zhang, Nicklas Hansen, Huazhe Xu, Xiaolong Wang |
| 2022 | Learning Weakly-supervised Contrastive Representations. Yao-Hung Hubert Tsai, Tianqin Li, Weixin Liu, Peiyuan Liao, Ruslan Salakhutdinov, Louis-Philippe Morency |
| 2022 | Learning a subspace of policies for online adaptation in Reinforcement Learning. Jean-Baptiste Gaya, Laure Soulier, Ludovic Denoyer |
| 2022 | Learning by Directional Gradient Descent. David Silver, Anirudh Goyal, Ivo Danihelka, Matteo Hessel, Hado van Hasselt |
| 2022 | Learning curves for continual learning in neural networks: Self-knowledge transfer and forgetting. Ryo Karakida, Shotaro Akaho |
| 2022 | Learning meta-features for AutoML. Herilalaina Rakotoarison, Louisot Milijaona, Andry Rasoanaivo, Michèle Sebag, Marc Schoenauer |
| 2022 | Learning more skills through optimistic exploration. DJ Strouse, Kate Baumli, David Warde-Farley, Volodymyr Mnih, Steven Stenberg Hansen |
| 2022 | Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks. Marten Lienen, Stephan Günnemann |
| 2022 | Learning to Annotate Part Segmentation with Gradient Matching. Yu Yang, Xiaotian Cheng, Hakan Bilen, Xiangyang Ji |
| 2022 | Learning to Complete Code with Sketches. Daya Guo, Alexey Svyatkovskiy, Jian Yin, Nan Duan, Marc Brockschmidt, Miltiadis Allamanis |
| 2022 | Learning to Dequantise with Truncated Flows. Shawn Tan, Chin-Wei Huang, Alessandro Sordoni, Aaron C. Courville |
| 2022 | Learning to Downsample for Segmentation of Ultra-High Resolution Images. Chen Jin, Ryutaro Tanno, Thomy Mertzanidou, Eleftheria Panagiotaki, Daniel C. Alexander |
| 2022 | Learning to Extend Molecular Scaffolds with Structural Motifs. Krzysztof Maziarz, Henry Richard Jackson-Flux, Pashmina Cameron, Finton Sirockin, Nadine Schneider, Nikolaus Stiefl, Marwin H. S. Segler, Marc Brockschmidt |
| 2022 | Learning to Generalize across Domains on Single Test Samples. Zehao Xiao, Xiantong Zhen, Ling Shao, Cees G. M. Snoek |
| 2022 | Learning to Guide and to be Guided in the Architect-Builder Problem. Paul Barde, Tristan Karch, Derek Nowrouzezahrai, Clément Moulin-Frier, Christopher Pal, Pierre-Yves Oudeyer |
| 2022 | Learning to Map for Active Semantic Goal Navigation. Georgios Georgakis, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Kostas Daniilidis |
| 2022 | Learning to Remember Patterns: Pattern Matching Memory Networks for Traffic Forecasting. Hyunwook Lee, Seungmin Jin, Hyeshin Chu, Hongkyu Lim, Sungahn Ko |
| 2022 | Learning to Schedule Learning rate with Graph Neural Networks. Yuanhao Xiong, Li-Cheng Lan, Xiangning Chen, Ruochen Wang, Cho-Jui Hsieh |
| 2022 | Learning transferable motor skills with hierarchical latent mixture policies. Dushyant Rao, Fereshteh Sadeghi, Leonard Hasenclever, Markus Wulfmeier, Martina Zambelli, Giulia Vezzani, Dhruva Tirumala, Yusuf Aytar, Josh Merel, Nicolas Heess, Raia Hadsell |
| 2022 | Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations. Jiaheng Wei, Zhaowei Zhu, Hao Cheng, Tongliang Liu, Gang Niu, Yang Liu |
| 2022 | Learning-Augmented $k$-means Clustering. Jon C. Ergun, Zhili Feng, Sandeep Silwal, David P. Woodruff, Samson Zhou |
| 2022 | Leveraging Automated Unit Tests for Unsupervised Code Translation. Baptiste Rozière, Jie Zhang, François Charton, Mark Harman, Gabriel Synnaeve, Guillaume Lample |
| 2022 | Leveraging unlabeled data to predict out-of-distribution performance. Saurabh Garg, Sivaraman Balakrishnan, Zachary Chase Lipton, Behnam Neyshabur, Hanie Sedghi |
| 2022 | Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory. Tianrong Chen, Guan-Horng Liu, Evangelos A. Theodorou |
| 2022 | Linking Emergent and Natural Languages via Corpus Transfer. Shunyu Yao, Mo Yu, Yang Zhang, Karthik R. Narasimhan, Joshua B. Tenenbaum, Chuang Gan |
| 2022 | Lipschitz-constrained Unsupervised Skill Discovery. Seohong Park, Jongwook Choi, Jaekyeom Kim, Honglak Lee, Gunhee Kim |
| 2022 | LoRA: Low-Rank Adaptation of Large Language Models. Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen |
| 2022 | Local Feature Swapping for Generalization in Reinforcement Learning. David Bertoin, Emmanuel Rachelson |
| 2022 | Long Expressive Memory for Sequence Modeling. T. Konstantin Rusch, Siddhartha Mishra, N. Benjamin Erichson, Michael W. Mahoney |
| 2022 | Looking Back on Learned Experiences For Class/task Incremental Learning. Mozhgan Pourkeshavarz, Guoying Zhao, Mohammad Sabokrou |
| 2022 | Lossless Compression with Probabilistic Circuits. Anji Liu, Stephan Mandt, Guy Van den Broeck |
| 2022 | Lossy Compression with Distribution Shift as Entropy Constrained Optimal Transport. Huan Liu, George Zhang, Jun Chen, Ashish J. Khisti |
| 2022 | Low-Budget Active Learning via Wasserstein Distance: An Integer Programming Approach. Rafid Mahmood, Sanja Fidler, Marc T. Law |
| 2022 | MAML is a Noisy Contrastive Learner in Classification. Chia-Hsiang Kao, Wei-Chen Chiu, Pin-Yu Chen |
| 2022 | MCMC Should Mix: Learning Energy-Based Model with Neural Transport Latent Space MCMC. Erik Nijkamp, Ruiqi Gao, Pavel Sountsov, Srinivas Vasudevan, Bo Pang, Song-Chun Zhu, Ying Nian Wu |
| 2022 | MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modeling. Yusong Wu, Ethan Manilow, Yi Deng, Rigel Swavely, Kyle Kastner, Tim Cooijmans, Aaron C. Courville, Cheng-Zhi Anna Huang, Jesse H. Engel |
| 2022 | MT3: Multi-Task Multitrack Music Transcription. Josh Gardner, Ian Simon, Ethan Manilow, Curtis Hawthorne, Jesse H. Engel |
| 2022 | MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining. Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk |
| 2022 | Machine Learning For Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality. Yiping Lu, Haoxuan Chen, Jianfeng Lu, Lexing Ying, Jose H. Blanchet |
| 2022 | Map Induction: Compositional spatial submap learning for efficient exploration in novel environments. Sugandha Sharma, Aidan Curtis, Marta Kryven, Joshua B. Tenenbaum, Ila R. Fiete |
| 2022 | Mapping Language Models to Grounded Conceptual Spaces. Roma Patel, Ellie Pavlick |
| 2022 | Mapping conditional distributions for domain adaptation under generalized target shift. Matthieu Kirchmeyer, Alain Rakotomamonjy, Emmanuel de Bézenac, Patrick Gallinari |
| 2022 | Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning. Denis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto |
| 2022 | Maximizing Ensemble Diversity in Deep Reinforcement Learning. Hassam Sheikh, Mariano Phielipp, Ladislau Bölöni |
| 2022 | Maximum Entropy RL (Provably) Solves Some Robust RL Problems. Benjamin Eysenbach, Sergey Levine |
| 2022 | Maximum n-times Coverage for Vaccine Design. Ge Liu, Alexander Dimitrakakis, Brandon Carter, David K. Gifford |
| 2022 | Measuring CLEVRness: Black-box Testing of Visual Reasoning Models. Spyridon Mouselinos, Henryk Michalewski, Mateusz Malinowski |
| 2022 | Measuring the Interpretability of Unsupervised Representations via Quantized Reversed Probing. Iro Laina, Yuki M. Asano, Andrea Vedaldi |
| 2022 | Memorizing Transformers. Yuhuai Wu, Markus Norman Rabe, DeLesley Hutchins, Christian Szegedy |
| 2022 | Memory Augmented Optimizers for Deep Learning. Paul-Aymeric Martin McRae, Prasanna Parthasarathi, Mido Assran, Sarath Chandar |
| 2022 | Memory Replay with Data Compression for Continual Learning. Liyuan Wang, Xingxing Zhang, Kuo Yang, Longhui Yu, Chongxuan Li, Lanqing Hong, Shifeng Zhang, Zhenguo Li, Yi Zhong, Jun Zhu |
| 2022 | Mention Memory: incorporating textual knowledge into Transformers through entity mention attention. Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Fei Sha, William W. Cohen |
| 2022 | Message Passing Neural PDE Solvers. Johannes Brandstetter, Daniel E. Worrall, Max Welling |
| 2022 | Meta Discovery: Learning to Discover Novel Classes given Very Limited Data. Haoang Chi, Feng Liu, Wenjing Yang, Long Lan, Tongliang Liu, Bo Han, Gang Niu, Mingyuan Zhou, Masashi Sugiyama |
| 2022 | Meta Learning Low Rank Covariance Factors for Energy Based Deterministic Uncertainty. Jeffrey Ryan Willette, Hae Beom Lee, Juho Lee, Sung Ju Hwang |
| 2022 | Meta-Imitation Learning by Watching Video Demonstrations. Jiayi Li, Tao Lu, Xiaoge Cao, Yinghao Cai, Shuo Wang |
| 2022 | Meta-Learning with Fewer Tasks through Task Interpolation. Huaxiu Yao, Linjun Zhang, Chelsea Finn |
| 2022 | MetaMorph: Learning Universal Controllers with Transformers. Agrim Gupta, Linxi Fan, Surya Ganguli, Li Fei-Fei |
| 2022 | MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts. Weixin Liang, James Zou |
| 2022 | Mind the Gap: Domain Gap Control for Single Shot Domain Adaptation for Generative Adversarial Networks. Peihao Zhu, Rameen Abdal, John Femiani, Peter Wonka |
| 2022 | Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond. Chulhee Yun, Shashank Rajput, Suvrit Sra |
| 2022 | Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs. Sitan Chen, Jerry Li, Yuanzhi Li, Raghu Meka |
| 2022 | Minimax Optimization with Smooth Algorithmic Adversaries. Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J. Ratliff |
| 2022 | Mirror Descent Policy Optimization. Manan Tomar, Lior Shani, Yonathan Efroni, Mohammad Ghavamzadeh |
| 2022 | Missingness Bias in Model Debugging. Saachi Jain, Hadi Salman, Eric Wong, Pengchuan Zhang, Vibhav Vineet, Sai Vemprala, Aleksander Madry |
| 2022 | MoReL: Multi-omics Relational Learning. Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Xiaoning Qian |
| 2022 | MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer. Sachin Mehta, Mohammad Rastegari |
| 2022 | Model Agnostic Interpretability for Multiple Instance Learning. Joseph Early, Christine Evers, Sarvapali D. Ramchurn |
| 2022 | Model Zoo: A Growing Brain That Learns Continually. Rahul Ramesh, Pratik Chaudhari |
| 2022 | Model-Based Offline Meta-Reinforcement Learning with Regularization. Sen Lin, Jialin Wan, Tengyu Xu, Yingbin Liang, Junshan Zhang |
| 2022 | Model-augmented Prioritized Experience Replay. Youngmin Oh, Jinwoo Shin, Eunho Yang, Sung Ju Hwang |
| 2022 | Modeling Label Space Interactions in Multi-label Classification using Box Embeddings. Dhruvesh Patel, Pavitra Dangati, Jay-Yoon Lee, Michael Boratko, Andrew McCallum |
| 2022 | Modular Lifelong Reinforcement Learning via Neural Composition. Jorge A. Mendez, Harm van Seijen, Eric Eaton |
| 2022 | MonoDistill: Learning Spatial Features for Monocular 3D Object Detection. Zhiyu Chong, Xinzhu Ma, Hong Zhang, Yuxin Yue, Haojie Li, Zhihui Wang, Wanli Ouyang |
| 2022 | Monotonic Differentiable Sorting Networks. Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen |
| 2022 | Multi-Agent MDP Homomorphic Networks. Elise van der Pol, Herke van Hoof, Frans A. Oliehoek, Max Welling |
| 2022 | Multi-Critic Actor Learning: Teaching RL Policies to Act with Style. Siddharth Mysore, George Cheng, Yunqi Zhao, Kate Saenko, Meng Wu |
| 2022 | Multi-Mode Deep Matrix and Tensor Factorization. Jicong Fan |
| 2022 | Multi-Stage Episodic Control for Strategic Exploration in Text Games. Jens Tuyls, Shunyu Yao, Sham M. Kakade, Karthik Narasimhan |
| 2022 | Multi-Task Processes. Donggyun Kim, Seongwoong Cho, Wonkwang Lee, Seunghoon Hong |
| 2022 | Multi-objective Optimization by Learning Space Partition. Yiyang Zhao, Linnan Wang, Kevin Yang, Tianjun Zhang, Tian Guo, Yuandong Tian |
| 2022 | Multimeasurement Generative Models. Saeed Saremi, Rupesh Kumar Srivastava |
| 2022 | Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation. Yan Zhang, David W. Zhang, Simon Lacoste-Julien, Gertjan J. Burghouts, Cees G. M. Snoek |
| 2022 | Multitask Prompted Training Enables Zero-Shot Task Generalization. Victor Sanh, Albert Webson, Colin Raffel, Stephen H. Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Arun Raja, Manan Dey, M Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal V. Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Févry, Jason Alan Fries, Ryan Teehan, Teven Le Scao, Stella Biderman, Leo Gao, Thomas Wolf, Alexander M. Rush |
| 2022 | NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy. Yash Mehta, Colin White, Arber Zela, Arjun Krishnakumar, Guri Zabergja, Shakiba Moradian, Mahmoud Safari, Kaicheng Yu, Frank Hutter |
| 2022 | NASI: Label- and Data-agnostic Neural Architecture Search at Initialization. Yao Shu, Shaofeng Cai, Zhongxiang Dai, Beng Chin Ooi, Bryan Kian Hsiang Low |
| 2022 | NASPY: Automated Extraction of Automated Machine Learning Models. Xiaoxuan Lou, Shangwei Guo, Jiwei Li, Yaoxin Wu, Tianwei Zhang |
| 2022 | NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training. Chengyue Gong, Dilin Wang, Meng Li, Xinlei Chen, Zhicheng Yan, Yuandong Tian, Qiang Liu, Vikas Chandra |
| 2022 | NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning. Chun-Hao Chang, Rich Caruana, Anna Goldenberg |
| 2022 | Natural Language Descriptions of Deep Visual Features. Evan Hernandez, Sarah Schwettmann, David Bau, Teona Bagashvili, Antonio Torralba, Jacob Andreas |
| 2022 | Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions. Bertrand Charpentier, Oliver Borchert, Daniel Zügner, Simon Geisler, Stephan Günnemann |
| 2022 | Near-Optimal Reward-Free Exploration for Linear Mixture MDPs with Plug-in Solver. Xiaoyu Chen, Jiachen Hu, Lin Yang, Liwei Wang |
| 2022 | Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism. Ming Yin, Yaqi Duan, Mengdi Wang, Yu-Xiang Wang |
| 2022 | Network Augmentation for Tiny Deep Learning. Han Cai, Chuang Gan, Ji Lin, Song Han |
| 2022 | Network Insensitivity to Parameter Noise via Parameter Attack During Training. Julian Büchel, Fynn Firouz Faber, Dylan Richard Muir |
| 2022 | NeuPL: Neural Population Learning. Siqi Liu, Luke Marris, Daniel Hennes, Josh Merel, Nicolas Heess, Thore Graepel |
| 2022 | Neural Collapse Under MSE Loss: Proximity to and Dynamics on the Central Path. X. Y. Han, Vardan Papyan, David L. Donoho |
| 2022 | Neural Contextual Bandits with Deep Representation and Shallow Exploration. Pan Xu, Zheng Wen, Handong Zhao, Quanquan Gu |
| 2022 | Neural Deep Equilibrium Solvers. Shaojie Bai, Vladlen Koltun, J. Zico Kolter |
| 2022 | Neural Link Prediction with Walk Pooling. Liming Pan, Cheng Shi, Ivan Dokmanic |
| 2022 | Neural Markov Controlled SDE: Stochastic Optimization for Continuous-Time Data. Sung Woo Park, Kyungjae Lee, Junseok Kwon |
| 2022 | Neural Methods for Logical Reasoning over Knowledge Graphs. Alfonso Amayuelas, Shuai Zhang, Susie Xi Rao, Ce Zhang |
| 2022 | Neural Models for Output-Space Invariance in Combinatorial Problems. Yatin Nandwani, Vidit Jain, Mausam, Parag Singla |
| 2022 | Neural Network Approximation based on Hausdorff distance of Tropical Zonotopes. Panagiotis Misiakos, Georgios Smyrnis, George Retsinas, Petros Maragos |
| 2022 | Neural Networks as Kernel Learners: The Silent Alignment Effect. Alexander B. Atanasov, Blake Bordelon, Cengiz Pehlevan |
| 2022 | Neural Parameter Allocation Search. Bryan A. Plummer, Nikoli Dryden, Julius Frost, Torsten Hoefler, Kate Saenko |
| 2022 | Neural Processes with Stochastic Attention: Paying more attention to the context dataset. Mingyu Kim, Kyeongryeol Go, Se-Young Yun |
| 2022 | Neural Program Synthesis with Query. Di Huang, Rui Zhang, Xing Hu, Xishan Zhang, Pengwei Jin, Nan Li, Zidong Du, Qi Guo, Yunji Chen |
| 2022 | Neural Relational Inference with Node-Specific Information. Ershad Banijamali |
| 2022 | Neural Solvers for Fast and Accurate Numerical Optimal Control. Federico Berto, Stefano Massaroli, Michael Poli, Jinkyoo Park |
| 2022 | Neural Spectral Marked Point Processes. Shixiang Zhu, Haoyun Wang, Zheng Dong, Xiuyuan Cheng, Yao Xie |
| 2022 | Neural Stochastic Dual Dynamic Programming. Hanjun Dai, Yuan Xue, Zia Syed, Dale Schuurmans, Bo Dai |
| 2022 | Neural Structured Prediction for Inductive Node Classification. Meng Qu, Huiyu Cai, Jian Tang |
| 2022 | Neural Variational Dropout Processes. Insu Jeon, Youngjin Park, Gunhee Kim |
| 2022 | Neural graphical modelling in continuous-time: consistency guarantees and algorithms. Alexis Bellot, Kim Branson, Mihaela van der Schaar |
| 2022 | New Insights on Reducing Abrupt Representation Change in Online Continual Learning. Lucas Caccia, Rahaf Aljundi, Nader Asadi, Tinne Tuytelaars, Joelle Pineau, Eugene Belilovsky |
| 2022 | No One Representation to Rule Them All: Overlapping Features of Training Methods. Raphael Gontijo Lopes, Yann N. Dauphin, Ekin Dogus Cubuk |
| 2022 | No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models. Chen Liang, Haoming Jiang, Simiao Zuo, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao |
| 2022 | Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction. Eli Chien, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Jiong Zhang, Olgica Milenkovic, Inderjit S. Dhillon |
| 2022 | NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs. Mikhail Galkin, Etienne G. Denis, Jiapeng Wu, William L. Hamilton |
| 2022 | Noisy Feature Mixup. Soon Hoe Lim, N. Benjamin Erichson, Francisco Utrera, Winnie Xu, Michael W. Mahoney |
| 2022 | Non-Linear Operator Approximations for Initial Value Problems. Gaurav Gupta, Xiongye Xiao, Radu Balan, Paul Bogdan |
| 2022 | Non-Parallel Text Style Transfer with Self-Parallel Supervision. Ruibo Liu, Chongyang Gao, Chenyan Jia, Guangxuan Xu, Soroush Vosoughi |
| 2022 | Non-Transferable Learning: A New Approach for Model Ownership Verification and Applicability Authorization. Lixu Wang, Shichao Xu, Ruiqi Xu, Xiao Wang, Qi Zhu |
| 2022 | Nonlinear ICA Using Volume-Preserving Transformations. Xiaojiang Yang, Yi Wang, Jiacheng Sun, Xing Zhang, Shifeng Zhang, Zhenguo Li, Junchi Yan |
| 2022 | Normalization of Language Embeddings for Cross-Lingual Alignment. Prince Osei Aboagye, Yan Zheng, Chin-Chia Michael Yeh, Junpeng Wang, Wei Zhang, Liang Wang, Hao Yang, Jeff M. Phillips |
| 2022 | Object Dynamics Distillation for Scene Decomposition and Representation. Qu Tang, Xiangyu Zhu, Zhen Lei, Zhaoxiang Zhang |
| 2022 | Object Pursuit: Building a Space of Objects via Discriminative Weight Generation. Chuanyu Pan, Yanchao Yang, Kaichun Mo, Yueqi Duan, Leonidas J. Guibas |
| 2022 | Objects in Semantic Topology. Shuo Yang, Peize Sun, Yi Jiang, Xiaobo Xia, Ruiheng Zhang, Zehuan Yuan, Changhu Wang, Ping Luo, Min Xu |
| 2022 | Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization. Thanh Nguyen-Tang, Sunil Gupta, A. Tuan Nguyen, Svetha Venkatesh |
| 2022 | Offline Reinforcement Learning with Implicit Q-Learning. Ilya Kostrikov, Ashvin Nair, Sergey Levine |
| 2022 | Offline Reinforcement Learning with Value-based Episodic Memory. Xiaoteng Ma, Yiqin Yang, Hao Hu, Jun Yang, Chongjie Zhang, Qianchuan Zhao, Bin Liang, Qihan Liu |
| 2022 | Omni-Dimensional Dynamic Convolution. Chao Li, Aojun Zhou, Anbang Yao |
| 2022 | Omni-Scale CNNs: a simple and effective kernel size configuration for time series classification. Wensi Tang, Guodong Long, Lu Liu, Tianyi Zhou, Michael Blumenstein, Jing Jiang |
| 2022 | On Bridging Generic and Personalized Federated Learning for Image Classification. Hong-You Chen, Wei-Lun Chao |
| 2022 | On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning. Guy Tennenholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik, Uri Shalit |
| 2022 | On Distributed Adaptive Optimization with Gradient Compression. Xiaoyun Li, Belhal Karimi, Ping Li |
| 2022 | On Evaluation Metrics for Graph Generative Models. Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham W. Taylor |
| 2022 | On Improving Adversarial Transferability of Vision Transformers. Muzammal Naseer, Kanchana Ranasinghe, Salman Khan, Fahad Shahbaz Khan, Fatih Porikli |
| 2022 | On Incorporating Inductive Biases into VAEs. Ning Miao, Emile Mathieu, Siddharth N, Yee Whye Teh, Tom Rainforth |
| 2022 | On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning. Marc Aurel Vischer, Robert Tjarko Lange, Henning Sprekeler |
| 2022 | On Non-Random Missing Labels in Semi-Supervised Learning. Xinting Hu, Yulei Niu, Chunyan Miao, Xian-Sheng Hua, Hanwang Zhang |
| 2022 | On Predicting Generalization using GANs. Yi Zhang, Arushi Gupta, Nikunj Saunshi, Sanjeev Arora |
| 2022 | On Redundancy and Diversity in Cell-based Neural Architecture Search. Xingchen Wan, Binxin Ru, Pedro M. Esperança, Zhenguo Li |
| 2022 | On Robust Prefix-Tuning for Text Classification. Zonghan Yang, Yang Liu |
| 2022 | On feature learning in neural networks with global convergence guarantees. Zhengdao Chen, Eric Vanden-Eijnden, Joan Bruna |
| 2022 | On the Certified Robustness for Ensemble Models and Beyond. Zhuolin Yang, Linyi Li, Xiaojun Xu, Bhavya Kailkhura, Tao Xie, Bo Li |
| 2022 | On the Connection between Local Attention and Dynamic Depth-wise Convolution. Qi Han, Zejia Fan, Qi Dai, Lei Sun, Ming-Ming Cheng, Jiaying Liu, Jingdong Wang |
| 2022 | On the Convergence of Certified Robust Training with Interval Bound Propagation. Yihan Wang, Zhouxing Shi, Quanquan Gu, Cho-Jui Hsieh |
| 2022 | On the Convergence of mSGD and AdaGrad for Stochastic Optimization. Ruinan Jin, Yu Xing, Xingkang He |
| 2022 | On the Convergence of the Monte Carlo Exploring Starts Algorithm for Reinforcement Learning. Che Wang, Shuhan Yuan, Kai Shao, Keith W. Ross |
| 2022 | On the Existence of Universal Lottery Tickets. Rebekka Burkholz, Nilanjana Laha, Rajarshi Mukherjee, Alkis Gotovos |
| 2022 | On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications. Ziqiao Wang, Yongyi Mao |
| 2022 | On the Importance of Difficulty Calibration in Membership Inference Attacks. Lauren Watson, Chuan Guo, Graham Cormode, Alexandre Sablayrolles |
| 2022 | On the Importance of Firth Bias Reduction in Few-Shot Classification. Saba Ghaffari, Ehsan Saleh, David A. Forsyth, Yu-Xiong Wang |
| 2022 | On the Learning and Learnability of Quasimetrics. Tongzhou Wang, Phillip Isola |
| 2022 | On the Limitations of Multimodal VAEs. Imant Daunhawer, Thomas M. Sutter, Kieran Chin-Cheong, Emanuele Palumbo, Julia E. Vogt |
| 2022 | On the Optimal Memorization Power of ReLU Neural Networks. Gal Vardi, Gilad Yehudai, Ohad Shamir |
| 2022 | On the Pitfalls of Analyzing Individual Neurons in Language Models. Omer Antverg, Yonatan Belinkov |
| 2022 | On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks. Maximilian Seitzer, Arash Tavakoli, Dimitrije Antic, Georg Martius |
| 2022 | On the Role of Neural Collapse in Transfer Learning. Tomer Galanti, András György, Marcus Hutter |
| 2022 | On the Uncomputability of Partition Functions in Energy-Based Sequence Models. Chu-Cheng Lin, Arya D. McCarthy |
| 2022 | On the approximation properties of recurrent encoder-decoder architectures. Zhong Li, Haotian Jiang, Qianxiao Li |
| 2022 | On the benefits of maximum likelihood estimation for Regression and Forecasting. Pranjal Awasthi, Abhimanyu Das, Rajat Sen, Ananda Theertha Suresh |
| 2022 | On the relation between statistical learning and perceptual distances. Alexander Hepburn, Valero Laparra, Raúl Santos-Rodríguez, Johannes Ballé, Jesus Malo |
| 2022 | On the role of population heterogeneity in emergent communication. Mathieu Rita, Florian Strub, Jean-Bastien Grill, Olivier Pietquin, Emmanuel Dupoux |
| 2022 | On-Policy Model Errors in Reinforcement Learning. Lukas P. Fröhlich, Maksym Lefarov, Melanie N. Zeilinger, Felix Berkenkamp |
| 2022 | One After Another: Learning Incremental Skills for a Changing World. Nur Muhammad (Mahi) Shafiullah, Lerrel Pinto |
| 2022 | Online Ad Hoc Teamwork under Partial Observability. Pengjie Gu, Mengchen Zhao, Jianye Hao, Bo An |
| 2022 | Online Adversarial Attacks. Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel |
| 2022 | Online Continual Learning on Class Incremental Blurry Task Configuration with Anytime Inference. Hyunseo Koh, Dahyun Kim, Jung-Woo Ha, Jonghyun Choi |
| 2022 | Online Coreset Selection for Rehearsal-based Continual Learning. Jaehong Yoon, Divyam Madaan, Eunho Yang, Sung Ju Hwang |
| 2022 | Online Facility Location with Predictions. Shaofeng H.-C. Jiang, Erzhi Liu, You Lyu, Zhihao Gavin Tang, Yubo Zhang |
| 2022 | Online Hyperparameter Meta-Learning with Hypergradient Distillation. Haebeom Lee, Hayeon Lee, Jaewoong Shin, Eunho Yang, Timothy M. Hospedales, Sung Ju Hwang |
| 2022 | Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs. Naman Agarwal, Syomantak Chaudhuri, Prateek Jain, Dheeraj Mysore Nagaraj, Praneeth Netrapalli |
| 2022 | OntoProtein: Protein Pretraining With Gene Ontology Embedding. Ningyu Zhang, Zhen Bi, Xiaozhuan Liang, Siyuan Cheng, Haosen Hong, Shumin Deng, Qiang Zhang, Jiazhang Lian, Huajun Chen |
| 2022 | Open-Set Recognition: A Good Closed-Set Classifier is All You Need. Sagar Vaze, Kai Han, Andrea Vedaldi, Andrew Zisserman |
| 2022 | Open-World Semi-Supervised Learning. Kaidi Cao, Maria Brbic, Jure Leskovec |
| 2022 | Open-vocabulary Object Detection via Vision and Language Knowledge Distillation. Xiuye Gu, Tsung-Yi Lin, Weicheng Kuo, Yin Cui |
| 2022 | Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks. Tong Bu, Wei Fang, Jianhao Ding, Penglin Dai, Zhaofei Yu, Tiejun Huang |
| 2022 | Optimal Representations for Covariate Shift. Yangjun Ruan, Yann Dubois, Chris J. Maddison |
| 2022 | Optimal Transport for Causal Discovery. Ruibo Tu, Kun Zhang, Hedvig Kjellström, Cheng Zhang |
| 2022 | Optimal Transport for Long-Tailed Recognition with Learnable Cost Matrix. Hanyu Peng, Mingming Sun, Ping Li |
| 2022 | Optimization and Adaptive Generalization of Three layer Neural Networks. Khashayar Gatmiry, Stefanie Jegelka, Jonathan A. Kelner |
| 2022 | Optimization inspired Multi-Branch Equilibrium Models. Mingjie Li, Yisen Wang, Xingyu Xie, Zhouchen Lin |
| 2022 | Optimizer Amalgamation. Tianshu Huang, Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang |
| 2022 | Optimizing Neural Networks with Gradient Lexicase Selection. Li Ding, Lee Spector |
| 2022 | Orchestrated Value Mapping for Reinforcement Learning. Mehdi Fatemi, Arash Tavakoli |
| 2022 | Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations. Aahlad Manas Puli, Lily H. Zhang, Eric Karl Oermann, Rajesh Ranganath |
| 2022 | Overcoming The Spectral Bias of Neural Value Approximation. Ge Yang, Anurag Ajay, Pulkit Agrawal |
| 2022 | P-Adapters: Robustly Extracting Factual Information from Language Models with Diverse Prompts. Benjamin Newman, Prafulla Kumar Choubey, Nazneen Rajani |
| 2022 | PAC Prediction Sets Under Covariate Shift. Sangdon Park, Edgar Dobriban, Insup Lee, Osbert Bastani |
| 2022 | PAC-Bayes Information Bottleneck. Zifeng Wang, Shao-Lun Huang, Ercan Engin Kuruoglu, Jimeng Sun, Xi Chen, Yefeng Zheng |
| 2022 | PEARL: Data Synthesis via Private Embeddings and Adversarial Reconstruction Learning. Seng Pei Liew, Tsubasa Takahashi, Michihiko Ueno |
| 2022 | PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning Method. Ziwei Guan, Tengyu Xu, Yingbin Liang |
| 2022 | PF-GNN: Differentiable particle filtering based approximation of universal graph representations. Mohammed Haroon Dupty, Yanfei Dong, Wee Sun Lee |
| 2022 | PI3NN: Out-of-distribution-aware Prediction Intervals from Three Neural Networks. Siyan Liu, Pei Zhang, Dan Lu, Guannan Zhang |
| 2022 | POETREE: Interpretable Policy Learning with Adaptive Decision Trees. Alizée Pace, Alex J. Chan, Mihaela van der Schaar |
| 2022 | PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series. Paul Jeha, Michael Bohlke-Schneider, Pedro Mercado, Shubham Kapoor, Rajbir-Singh Nirwan, Valentin Flunkert, Jan Gasthaus, Tim Januschowski |
| 2022 | Parallel Training of GRU Networks with a Multi-Grid Solver for Long Sequences. Euhyun Moon, Eric C. Cyr |
| 2022 | Pareto Policy Adaptation. Panagiotis Kyriakis, Jyotirmoy Deshmukh, Paul Bogdan |
| 2022 | Pareto Policy Pool for Model-based Offline Reinforcement Learning. Yijun Yang, Jing Jiang, Tianyi Zhou, Jie Ma, Yuhui Shi |
| 2022 | Pareto Set Learning for Neural Multi-Objective Combinatorial Optimization. Xi Lin, Zhiyuan Yang, Qingfu Zhang |
| 2022 | Partial Wasserstein Adversarial Network for Non-rigid Point Set Registration. Ziming Wang, Nan Xue, Ling Lei, Gui-Song Xia |
| 2022 | Particle Stochastic Dual Coordinate Ascent: Exponential convergent algorithm for mean field neural network optimization. Kazusato Oko, Taiji Suzuki, Atsushi Nitanda, Denny Wu |
| 2022 | Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations? Yonggan Fu, Shunyao Zhang, Shang Wu, Cheng Wan, Yingyan Lin |
| 2022 | Path Auxiliary Proposal for MCMC in Discrete Space. Haoran Sun, Hanjun Dai, Wei Xia, Arun Ramamurthy |
| 2022 | Path Integral Sampler: A Stochastic Control Approach For Sampling. Qinsheng Zhang, Yongxin Chen |
| 2022 | Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently. Xiaohan Chen, Jason Zhang, Zhangyang Wang |
| 2022 | Perceiver IO: A General Architecture for Structured Inputs & Outputs. Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier J. Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira |
| 2022 | Permutation Compressors for Provably Faster Distributed Nonconvex Optimization. Rafal Szlendak, Alexander Tyurin, Peter Richtárik |
| 2022 | Permutation-Based SGD: Is Random Optimal? Shashank Rajput, Kangwook Lee, Dimitris S. Papailiopoulos |
| 2022 | Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning. Chenjia Bai, Lingxiao Wang, Zhuoran Yang, Zhi-Hong Deng, Animesh Garg, Peng Liu, Zhaoran Wang |
| 2022 | Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage. Masatoshi Uehara, Wen Sun |
| 2022 | Phase Collapse in Neural Networks. Florentin Guth, John Zarka, Stéphane Mallat |
| 2022 | Phenomenology of Double Descent in Finite-Width Neural Networks. Sidak Pal Singh, Aurélien Lucchi, Thomas Hofmann, Bernhard Schölkopf |
| 2022 | PiCO: Contrastive Label Disambiguation for Partial Label Learning. Haobo Wang, Ruixuan Xiao, Yixuan Li, Lei Feng, Gang Niu, Gang Chen, Junbo Zhao |
| 2022 | PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication. Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin |
| 2022 | Pix2seq: A Language Modeling Framework for Object Detection. Ting Chen, Saurabh Saxena, Lala Li, David J. Fleet, Geoffrey E. Hinton |
| 2022 | Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models. Beidi Chen, Tri Dao, Kaizhao Liang, Jiaming Yang, Zhao Song, Atri Rudra, Christopher Ré |
| 2022 | Planning in Stochastic Environments with a Learned Model. Ioannis Antonoglou, Julian Schrittwieser, Sherjil Ozair, Thomas K. Hubert, David Silver |
| 2022 | Plant 'n' Seek: Can You Find the Winning Ticket? Jonas Fischer, Rebekka Burkholz |
| 2022 | PoNet: Pooling Network for Efficient Token Mixing in Long Sequences. Chao-Hong Tan, Qian Chen, Wen Wang, Qinglin Zhang, Siqi Zheng, Zhen-Hua Ling |
| 2022 | Poisoning and Backdooring Contrastive Learning. Nicholas Carlini, Andreas Terzis |
| 2022 | Policy Gradients Incorporating the Future. David Venuto, Elaine Lau, Doina Precup, Ofir Nachum |
| 2022 | Policy Smoothing for Provably Robust Reinforcement Learning. Aounon Kumar, Alexander Levine, Soheil Feizi |
| 2022 | Policy improvement by planning with Gumbel. Ivo Danihelka, Arthur Guez, Julian Schrittwieser, David Silver |
| 2022 | PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions. Zhaoqi Leng, Mingxing Tan, Chenxi Liu, Ekin Dogus Cubuk, Jay Shi, Shuyang Cheng, Dragomir Anguelov |
| 2022 | Possibility Before Utility: Learning And Using Hierarchical Affordances. Robby Costales, Shariq Iqbal, Fei Sha |
| 2022 | Post hoc Explanations may be Ineffective for Detecting Unknown Spurious Correlation. Julius Adebayo, Michael Muelly, Harold Abelson, Been Kim |
| 2022 | Post-Training Detection of Backdoor Attacks for Two-Class and Multi-Attack Scenarios. Zhen Xiang, David J. Miller, George Kesidis |
| 2022 | Practical Conditional Neural Process Via Tractable Dependent Predictions. Stratis Markou, James Requeima, Wessel P. Bruinsma, Anna Vaughan, Richard E. Turner |
| 2022 | Practical Integration via Separable Bijective Networks. Christopher M. Bender, Patrick Emmanuel, Michael K. Reiter, Junier Oliva |
| 2022 | Pre-training Molecular Graph Representation with 3D Geometry. Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang |
| 2022 | Predicting Physics in Mesh-reduced Space with Temporal Attention. Xu Han, Han Gao, Tobias Pfaff, Jian-Xun Wang, Liping Liu |
| 2022 | Pretrained Language Model in Continual Learning: A Comparative Study. Tongtong Wu, Massimo Caccia, Zhuang Li, Yuan-Fang Li, Guilin Qi, Gholamreza Haffari |
| 2022 | Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators. Yu Meng, Chenyan Xiong, Payal Bajaj, Saurabh Tiwary, Paul N. Bennett, Jiawei Han, Xia Song |
| 2022 | PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior. Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu |
| 2022 | Privacy Implications of Shuffling. Casey Meehan, Amrita Roy Chowdhury, Kamalika Chaudhuri, Somesh Jha |
| 2022 | Probabilistic Implicit Scene Completion. Dongsu Zhang, Changwoon Choi, Inbum Park, Young Min Kim |
| 2022 | Procedural generalization by planning with self-supervised world models. Ankesh Anand, Jacob C. Walker, Yazhe Li, Eszter Vértes, Julian Schrittwieser, Sherjil Ozair, Theophane Weber, Jessica B. Hamrick |
| 2022 | Programmatic Reinforcement Learning without Oracles. Wenjie Qiu, He Zhu |
| 2022 | Progressive Distillation for Fast Sampling of Diffusion Models. Tim Salimans, Jonathan Ho |
| 2022 | Promoting Saliency From Depth: Deep Unsupervised RGB-D Saliency Detection. Wei Ji, Jingjing Li, Qi Bi, Chuan Guo, Jie Liu, Li Cheng |
| 2022 | Proof Artifact Co-Training for Theorem Proving with Language Models. Jesse Michael Han, Jason Rute, Yuhuai Wu, Edward W. Ayers, Stanislas Polu |
| 2022 | Properties from mechanisms: an equivariance perspective on identifiable representation learning. Kartik Ahuja, Jason S. Hartford, Yoshua Bengio |
| 2022 | Prospect Pruning: Finding Trainable Weights at Initialization using Meta-Gradients. Milad Alizadeh, Shyam A. Tailor, Luisa M. Zintgraf, Joost van Amersfoort, Sebastian Farquhar, Nicholas Donald Lane, Yarin Gal |
| 2022 | ProtoRes: Proto-Residual Network for Pose Authoring via Learned Inverse Kinematics. Boris N. Oreshkin, Florent Bocquelet, Félix G. Harvey, Bay Raitt, Dominic Laflamme |
| 2022 | Prototype memory and attention mechanisms for few shot image generation. Tianqin Li, Zijie Li, Andrew Luo, Harold Rockwell, Amir Barati Farimani, Tai Sing Lee |
| 2022 | Prototypical Contrastive Predictive Coding. Kyungmin Lee |
| 2022 | Provable Adaptation across Multiway Domains via Representation Learning. Zhili Feng, Shaobo Han, Simon Shaolei Du |
| 2022 | Provable Learning-based Algorithm For Sparse Recovery. Xinshi Chen, Haoran Sun, Le Song |
| 2022 | Provably Filtering Exogenous Distractors using Multistep Inverse Dynamics. Yonathan Efroni, Dipendra Misra, Akshay Krishnamurthy, Alekh Agarwal, John Langford |
| 2022 | Provably Robust Adversarial Examples. Dimitar Iliev Dimitrov, Gagandeep Singh, Timon Gehr, Martin T. Vechev |
| 2022 | Provably convergent quasistatic dynamics for mean-field two-player zero-sum games. Chao Ma, Lexing Ying |
| 2022 | Proving the Lottery Ticket Hypothesis for Convolutional Neural Networks. Arthur da Cunha, Emanuele Natale, Laurent Viennot |
| 2022 | Pseudo Numerical Methods for Diffusion Models on Manifolds. Luping Liu, Yi Ren, Zhijie Lin, Zhou Zhao |
| 2022 | Pseudo-Labeled Auto-Curriculum Learning for Semi-Supervised Keypoint Localization. Can Wang, Sheng Jin, Yingda Guan, Wentao Liu, Chen Qian, Ping Luo, Wanli Ouyang |
| 2022 | Pyraformer: Low-Complexity Pyramidal Attention for Long-Range Time Series Modeling and Forecasting. Shizhan Liu, Hang Yu, Cong Liao, Jianguo Li, Weiyao Lin, Alex X. Liu, Schahram Dustdar |
| 2022 | QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization. Xiuying Wei, Ruihao Gong, Yuhang Li, Xianglong Liu, Fengwei Yu |
| 2022 | Quadtree Attention for Vision Transformers. Shitao Tang, Jiahui Zhang, Siyu Zhu, Ping Tan |
| 2022 | Quantitative Performance Assessment of CNN Units via Topological Entropy Calculation. Yang Zhao, Hao Zhang |
| 2022 | Query Efficient Decision Based Sparse Attacks Against Black-Box Deep Learning Models. Viet Quoc Vo, Ehsan Abbasnejad, Damith Ranasinghe |
| 2022 | Query Embedding on Hyper-Relational Knowledge Graphs. Dimitrios Alivanistos, Max Berrendorf, Michael Cochez, Mikhail Galkin |
| 2022 | R4D: Utilizing Reference Objects for Long-Range Distance Estimation. Yingwei Li, Tiffany L. Chen, Maya Kabkab, Ruichi Yu, Longlong Jing, Yurong You, Hang Zhao |
| 2022 | R5: Rule Discovery with Reinforced and Recurrent Relational Reasoning. Shengyao Lu, Bang Liu, Keith G. Mills, Shangling Jui, Di Niu |
| 2022 | RISP: Rendering-Invariant State Predictor with Differentiable Simulation and Rendering for Cross-Domain Parameter Estimation. Pingchuan Ma, Tao Du, Joshua B. Tenenbaum, Wojciech Matusik, Chuang Gan |
| 2022 | Random matrices in service of ML footprint: ternary random features with no performance loss. Hafiz Tiomoko Ali, Zhenyu Liao, Romain Couillet |
| 2022 | Real-Time Neural Voice Camouflage. Mia Chiquier, Chengzhi Mao, Carl Vondrick |
| 2022 | Recursive Disentanglement Network. Yixuan Chen, Yubin Shi, Dongsheng Li, Yujiang Wang, Mingzhi Dong, Yingying Zhao, Robert P. Dick, Qin Lv, Fan Yang, Li Shang |
| 2022 | Recycling Model Updates in Federated Learning: Are Gradient Subspaces Low-Rank? Sheikh Shams Azam, Seyyedali Hosseinalipour, Qiang Qiu, Christopher G. Brinton |
| 2022 | Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off. Rahul Rade, Seyed-Mohsen Moosavi-Dezfooli |
| 2022 | RegionViT: Regional-to-Local Attention for Vision Transformers. Chun-Fu Chen, Rameswar Panda, Quanfu Fan |
| 2022 | Regularized Autoencoders for Isometric Representation Learning. Yonghyeon Lee, Sangwoong Yoon, Minjun Son, Frank Chongwoo Park |
| 2022 | Reinforcement Learning in Presence of Discrete Markovian Context Evolution. Hang Ren, Aivar Sootla, Taher Jafferjee, Junxiao Shen, Jun Wang, Haitham Bou-Ammar |
| 2022 | Reinforcement Learning under a Multi-agent Predictive State Representation Model: Method and Theory. Zhi Zhang, Zhuoran Yang, Han Liu, Pratap Tokekar, Furong Huang |
| 2022 | Reinforcement Learning with Sparse Rewards using Guidance from Offline Demonstration. Desik Rengarajan, Gargi Vaidya, Akshay Sarvesh, Dileep M. Kalathil, Srinivas Shakkottai |
| 2022 | RelViT: Concept-guided Vision Transformer for Visual Relational Reasoning. Xiaojian Ma, Weili Nie, Zhiding Yu, Huaizu Jiang, Chaowei Xiao, Yuke Zhu, Song-Chun Zhu, Anima Anandkumar |
| 2022 | Relating transformers to models and neural representations of the hippocampal formation. James C. R. Whittington, Joseph Warren, Tim E. J. Behrens |
| 2022 | Relational Learning with Variational Bayes. Kuang-Hung Liu |
| 2022 | Relational Multi-Task Learning: Modeling Relations between Data and Tasks. Kaidi Cao, Jiaxuan You, Jure Leskovec |
| 2022 | Relational Surrogate Loss Learning. Tao Huang, Zekang Li, Hua Lu, Yong Shan, Shusheng Yang, Yang Feng, Fei Wang, Shan You, Chang Xu |
| 2022 | RelaxLoss: Defending Membership Inference Attacks without Losing Utility. Dingfan Chen, Ning Yu, Mario Fritz |
| 2022 | Reliable Adversarial Distillation with Unreliable Teachers. Jianing Zhu, Jiangchao Yao, Bo Han, Jingfeng Zhang, Tongliang Liu, Gang Niu, Jingren Zhou, Jianliang Xu, Hongxia Yang |
| 2022 | Representation Learning for Online and Offline RL in Low-rank MDPs. Masatoshi Uehara, Xuezhou Zhang, Wen Sun |
| 2022 | Representation-Agnostic Shape Fields. Xiaoyang Huang, Jiancheng Yang, Yanjun Wang, Ziyu Chen, Linguo Li, Teng Li, Bingbing Ni, Wenjun Zhang |
| 2022 | Representational Continuity for Unsupervised Continual Learning. Divyam Madaan, Jaehong Yoon, Yuanchun Li, Yunxin Liu, Sung Ju Hwang |
| 2022 | Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings. Dongsheng Wang, Dandan Guo, He Zhao, Huangjie Zheng, Korawat Tanwisuth, Bo Chen, Mingyuan Zhou |
| 2022 | Resolving Training Biases via Influence-based Data Relabeling. Shuming Kong, Yanyan Shen, Linpeng Huang |
| 2022 | Resonance in Weight Space: Covariate Shift Can Drive Divergence of SGD with Momentum. Kirby Banman, Liam Peet-Pare, Nidhi Hegde, Alona Fyshe, Martha White |
| 2022 | Responsible Disclosure of Generative Models Using Scalable Fingerprinting. Ning Yu, Vladislav Skripniuk, Dingfan Chen, Larry S. Davis, Mario Fritz |
| 2022 | Rethinking Adversarial Transferability from a Data Distribution Perspective. Yao Zhu, Jiacheng Sun, Zhenguo Li |
| 2022 | Rethinking Class-Prior Estimation for Positive-Unlabeled Learning. Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu, Masashi Sugiyama, Dacheng Tao |
| 2022 | Rethinking Goal-Conditioned Supervised Learning and Its Connection to Offline RL. Rui Yang, Yiming Lu, Wenzhe Li, Hao Sun, Meng Fang, Yali Du, Xiu Li, Lei Han, Chongjie Zhang |
| 2022 | Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework. Xu Ma, Can Qin, Haoxuan You, Haoxi Ran, Yun Fu |
| 2022 | Rethinking Supervised Pre-Training for Better Downstream Transferring. Yutong Feng, Jianwen Jiang, Mingqian Tang, Rong Jin, Yue Gao |
| 2022 | Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph. Dacheng Yin, Xuanchi Ren, Chong Luo, Yuwang Wang, Zhiwei Xiong, Wenjun Zeng |
| 2022 | Reverse Engineering of Imperceptible Adversarial Image Perturbations. Yifan Gong, Yuguang Yao, Yize Li, Yimeng Zhang, Xiaoming Liu, Xue Lin, Sijia Liu |
| 2022 | Reversible Instance Normalization for Accurate Time-Series Forecasting against Distribution Shift. Taesung Kim, Jinhee Kim, Yunwon Tae, Cheonbok Park, Jang-Ho Choi, Jaegul Choo |
| 2022 | Revisit Kernel Pruning with Lottery Regulated Grouped Convolutions. Shaochen (Henry) Zhong, Guanqun Zhang, Ningjia Huang, Shuai Xu |
| 2022 | Revisiting Design Choices in Offline Model Based Reinforcement Learning. Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts |
| 2022 | Revisiting Over-smoothing in BERT from the Perspective of Graph. Han Shi, Jiahui Gao, Hang Xu, Xiaodan Liang, Zhenguo Li, Lingpeng Kong, Stephen M. S. Lee, James T. Kwok |
| 2022 | Revisiting flow generative models for Out-of-distribution detection. Dihong Jiang, Sun Sun, Yaoliang Yu |
| 2022 | Reward Uncertainty for Exploration in Preference-based Reinforcement Learning. Xinran Liang, Katherine Shu, Kimin Lee, Pieter Abbeel |
| 2022 | Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models. Liam H. Fowl, Jonas Geiping, Wojciech Czaja, Micah Goldblum, Tom Goldstein |
| 2022 | Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness? Vikash Sehwag, Saeed Mahloujifar, Tinashe Handina, Sihui Dai, Chong Xiang, Mung Chiang, Prateek Mittal |
| 2022 | Robust Unlearnable Examples: Protecting Data Privacy Against Adversarial Learning. Shaopeng Fu, Fengxiang He, Yang Liu, Li Shen, Dacheng Tao |
| 2022 | Robust and Scalable SDE Learning: A Functional Perspective. Scott Alexander Cameron, Tyron Luke Cameron, Arnu Pretorius, Stephen J. Roberts |
| 2022 | RotoGrad: Gradient Homogenization in Multitask Learning. Adrián Javaloy, Isabel Valera |
| 2022 | RvS: What is Essential for Offline RL via Supervised Learning? Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov, Sergey Levine |
| 2022 | SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations. Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, Stefano Ermon |
| 2022 | SGD Can Converge to Local Maxima. Liu Ziyin, Botao Li, James B. Simon, Masahito Ueda |
| 2022 | SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models. Zaccharie Ramzi, Florian Mannel, Shaojie Bai, Jean-Luc Starck, Philippe Ciuciu, Thomas Moreau |
| 2022 | SOSP: Efficiently Capturing Global Correlations by Second-Order Structured Pruning. Manuel Nonnenmacher, Thomas Pfeil, Ingo Steinwart, David Reeb |
| 2022 | SPIRAL: Self-supervised Perturbation-Invariant Representation Learning for Speech Pre-Training. Wenyong Huang, Zhenhe Zhang, Yu Ting Yeung, Xin Jiang, Qun Liu |
| 2022 | SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation. Cong Guo, Yuxian Qiu, Jingwen Leng, Xiaotian Gao, Chen Zhang, Yunxin Liu, Fan Yang, Yuhao Zhu, Minyi Guo |
| 2022 | SUMNAS: Supernet with Unbiased Meta-Features for Neural Architecture Search. Hyeonmin Ha, Ji-Hoon Kim, Semin Park, Byung-Gon Chun |
| 2022 | SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning. Jongjin Park, Younggyo Seo, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee |
| 2022 | Safe Neurosymbolic Learning with Differentiable Symbolic Execution. Chenxi Yang, Swarat Chaudhuri |
| 2022 | Salient ImageNet: How to discover spurious features in Deep Learning? Sahil Singla, Soheil Feizi |
| 2022 | Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation. Vincent Mai, Kaustubh Mani, Liam Paull |
| 2022 | Sample Efficient Stochastic Policy Extragradient Algorithm for Zero-Sum Markov Game. Ziyi Chen, Shaocong Ma, Yi Zhou |
| 2022 | Sample Selection with Uncertainty of Losses for Learning with Noisy Labels. Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Jun Yu, Gang Niu, Masashi Sugiyama |
| 2022 | Sample and Computation Redistribution for Efficient Face Detection. Jia Guo, Jiankang Deng, Alexandros Lattas, Stefanos Zafeiriou |
| 2022 | Sampling with Mirrored Stein Operators. Jiaxin Shi, Chang Liu, Lester Mackey |
| 2022 | Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation. Ross M. Clarke, Elre Talea Oldewage, José Miguel Hernández-Lobato |
| 2022 | Scalable Sampling for Nonsymmetric Determinantal Point Processes. Insu Han, Mike Gartrell, Jennifer Gillenwater, Elvis Dohmatob, Amin Karbasi |
| 2022 | Scale Efficiently: Insights from Pretraining and Finetuning Transformers. Yi Tay, Mostafa Dehghani, Jinfeng Rao, William Fedus, Samira Abnar, Hyung Won Chung, Sharan Narang, Dani Yogatama, Ashish Vaswani, Donald Metzler |
| 2022 | Scale Mixtures of Neural Network Gaussian Processes. Hyungi Lee, EungGu Yun, Hongseok Yang, Juho Lee |
| 2022 | Scaling Laws for Neural Machine Translation. Behrooz Ghorbani, Orhan Firat, Markus Freitag, Ankur Bapna, Maxim Krikun, Xavier Garcia, Ciprian Chelba, Colin Cherry |
| 2022 | Scarf: Self-Supervised Contrastive Learning using Random Feature Corruption. Dara Bahri, Heinrich Jiang, Yi Tay, Donald Metzler |
| 2022 | Scattering Networks on the Sphere for Scalable and Rotationally Equivariant Spherical CNNs. Jason D. McEwen, Christopher G. R. Wallis, Augustine N. Mavor-Parker |
| 2022 | Scene Transformer: A unified architecture for predicting future trajectories of multiple agents. Jiquan Ngiam, Vijay Vasudevan, Benjamin Caine, Zhengdong Zhang, Hao-Tien Lewis Chiang, Jeffrey Ling, Rebecca Roelofs, Alex Bewley, Chenxi Liu, Ashish Venugopal, David J. Weiss, Ben Sapp, Zhifeng Chen, Jonathon Shlens |
| 2022 | Score-Based Generative Modeling with Critically-Damped Langevin Diffusion. Tim Dockhorn, Arash Vahdat, Karsten Kreis |
| 2022 | Selective Ensembles for Consistent Predictions. Emily Black, Klas Leino, Matt Fredrikson |
| 2022 | Self-Joint Supervised Learning. Navid Kardan, Mubarak Shah, Mitch Hill |
| 2022 | Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis. Siyi Tang, Jared Dunnmon, Khaled Kamal Saab, Xuan Zhang, Qianying Huang, Florian Dubost, Daniel L. Rubin, Christopher Lee-Messer |
| 2022 | Self-Supervised Inference in State-Space Models. David Ruhe, Patrick Forré |
| 2022 | Self-Supervision Enhanced Feature Selection with Correlated Gates. Changhee Lee, Fergus Imrie, Mihaela van der Schaar |
| 2022 | Self-ensemble Adversarial Training for Improved Robustness. Hongjun Wang, Yisen Wang |
| 2022 | Self-supervised Learning is More Robust to Dataset Imbalance. Hong Liu, Jeff Z. HaoChen, Adrien Gaidon, Tengyu Ma |
| 2022 | Semi-relaxed Gromov-Wasserstein divergence and applications on graphs. Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty |
| 2022 | Sequence Approximation using Feedforward Spiking Neural Network for Spatiotemporal Learning: Theory and Optimization Methods. Xueyuan She, Saurabh Dash, Saibal Mukhopadhyay |
| 2022 | Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning. Seanie Lee, Haebeom Lee, Juho Lee, Sung Ju Hwang |
| 2022 | Shallow and Deep Networks are Near-Optimal Approximators of Korobov Functions. Moïse Blanchard, Mohammed Amine Bennouna |
| 2022 | Should I Run Offline Reinforcement Learning or Behavioral Cloning? Aviral Kumar, Joey Hong, Anikait Singh, Sergey Levine |
| 2022 | Should We Be Pre-training? An Argument for End-task Aware Training as an Alternative. Lucio M. Dery, Paul Michel, Ameet Talwalkar, Graham Neubig |
| 2022 | Shuffle Private Stochastic Convex Optimization. Albert Cheu, Matthew Joseph, Jieming Mao, Binghui Peng |
| 2022 | Signing the Supermask: Keep, Hide, Invert. Nils Koster, Oliver Grothe, Achim Rettinger |
| 2022 | SimVLM: Simple Visual Language Model Pretraining with Weak Supervision. Zirui Wang, Jiahui Yu, Adams Wei Yu, Zihang Dai, Yulia Tsvetkov, Yuan Cao |
| 2022 | Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond. Jonathan Godwin, Michael Schaarschmidt, Alexander L. Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Velickovic, James Kirkpatrick, Peter W. Battaglia |
| 2022 | SketchODE: Learning neural sketch representation in continuous time. Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song |
| 2022 | Skill-based Meta-Reinforcement Learning. Taewook Nam, Shao-Hua Sun, Karl Pertsch, Sung Ju Hwang, Joseph J. Lim |
| 2022 | Solving Inverse Problems in Medical Imaging with Score-Based Generative Models. Yang Song, Liyue Shen, Lei Xing, Stefano Ermon |
| 2022 | Sound Adversarial Audio-Visual Navigation. Yinfeng Yu, Wenbing Huang, Fuchun Sun, Changan Chen, Yikai Wang, Xiaohong Liu |
| 2022 | Sound and Complete Neural Network Repair with Minimality and Locality Guarantees. Feisi Fu, Wenchao Li |
| 2022 | Source-Free Adaptation to Measurement Shift via Bottom-Up Feature Restoration. Cian Eastwood, Ian Mason, Christopher K. I. Williams, Bernhard Schölkopf |
| 2022 | Space-Time Graph Neural Networks. Samar Hadou, Charilaos I. Kanatsoulis, Alejandro Ribeiro |
| 2022 | Spanning Tree-based Graph Generation for Molecules. Sungsoo Ahn, Binghong Chen, Tianzhe Wang, Le Song |
| 2022 | Sparse Attention with Learning to Hash. Zhiqing Sun, Yiming Yang, Shinjae Yoo |
| 2022 | Sparse Communication via Mixed Distributions. António Farinhas, Wilker Aziz, Vlad Niculae, André F. T. Martins |
| 2022 | Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity. Byungseok Roh, Jaewoong Shin, Wuhyun Shin, Saehoon Kim |
| 2022 | Sparsity Winning Twice: Better Robust Generalization from More Efficient Training. Tianlong Chen, Zhenyu Zhang, Pengjun Wang, Santosh Balachandra, Haoyu Ma, Zehao Wang, Zhangyang Wang |
| 2022 | Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery. Yulun Wu, Nicholas Choma, Andrew Deru Chen, Mikaela Cashman, Érica Teixeira Prates, Verónica G. Melesse Vergara, Manesh Shah, Austin Clyde, Thomas S. Brettin, Wibe Albert de Jong, Neeraj Kumar, Martha S. Head, Rick L. Stevens, Peter Nugent, Daniel A. Jacobson, James B. Brown |
| 2022 | SphereFace2: Binary Classification is All You Need for Deep Face Recognition. Yandong Wen, Weiyang Liu, Adrian Weller, Bhiksha Raj, Rita Singh |
| 2022 | Spherical Message Passing for 3D Molecular Graphs. Yi Liu, Limei Wang, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, Shuiwang Ji |
| 2022 | Spike-inspired rank coding for fast and accurate recurrent neural networks. Alan Jeffares, Qinghai Guo, Pontus Stenetorp, Timoleon Moraitis |
| 2022 | Spread Spurious Attribute: Improving Worst-group Accuracy with Spurious Attribute Estimation. Jun Hyun Nam, Jaehyung Kim, Jaeho Lee, Jinwoo Shin |
| 2022 | Sqrt(d) Dimension Dependence of Langevin Monte Carlo. Ruilin Li, Hongyuan Zha, Molei Tao |
| 2022 | Stability Regularization for Discrete Representation Learning. Adeel Pervez, Efstratios Gavves |
| 2022 | Steerable Partial Differential Operators for Equivariant Neural Networks. Erik Jenner, Maurice Weiler |
| 2022 | Stein Latent Optimization for Generative Adversarial Networks. Uiwon Hwang, Heeseung Kim, Dahuin Jung, Hyemi Jang, Hyungyu Lee, Sungroh Yoon |
| 2022 | Step-unrolled Denoising Autoencoders for Text Generation. Nikolay Savinov, Junyoung Chung, Mikolaj Binkowski, Erich Elsen, Aäron van den Oord |
| 2022 | Stiffness-aware neural network for learning Hamiltonian systems. Senwei Liang, Zhongzhan Huang, Hong Zhang |
| 2022 | Stochastic Training is Not Necessary for Generalization. Jonas Geiping, Micah Goldblum, Phillip Pope, Michael Moeller, Tom Goldstein |
| 2022 | Strength of Minibatch Noise in SGD. Liu Ziyin, Kangqiao Liu, Takashi Mori, Masahito Ueda |
| 2022 | Structure-Aware Transformer Policy for Inhomogeneous Multi-Task Reinforcement Learning. Sunghoon Hong, Deunsol Yoon, Kee-Eung Kim |
| 2022 | StyleAlign: Analysis and Applications of Aligned StyleGAN Models. Zongze Wu, Yotam Nitzan, Eli Shechtman, Dani Lischinski |
| 2022 | StyleNeRF: A Style-based 3D Aware Generator for High-resolution Image Synthesis. Jiatao Gu, Lingjie Liu, Peng Wang, Christian Theobalt |
| 2022 | Subspace Regularizers for Few-Shot Class Incremental Learning. Afra Feyza Akyürek, Ekin Akyürek, Derry Wijaya, Jacob Andreas |
| 2022 | Superclass-Conditional Gaussian Mixture Model For Learning Fine-Grained Embeddings. Jingchao Ni, Wei Cheng, Zhengzhang Chen, Takayoshi Asakura, Tomoya Soma, Sho Kato, Haifeng Chen |
| 2022 | Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm. Yangguang Li, Feng Liang, Lichen Zhao, Yufeng Cui, Wanli Ouyang, Jing Shao, Fengwei Yu, Junjie Yan |
| 2022 | Surreal-GAN: Semi-Supervised Representation Learning via GAN for uncovering heterogeneous disease-related imaging patterns. Zhijian Yang, Junhao Wen, Christos Davatzikos |
| 2022 | Surrogate Gap Minimization Improves Sharpness-Aware Training. Juntang Zhuang, Boqing Gong, Liangzhe Yuan, Yin Cui, Hartwig Adam, Nicha C. Dvornek, Sekhar Tatikonda, James S. Duncan, Ting Liu |
| 2022 | Surrogate NAS Benchmarks: Going Beyond the Limited Search Spaces of Tabular NAS Benchmarks. Arber Zela, Julien Niklas Siems, Lucas Zimmer, Jovita Lukasik, Margret Keuper, Frank Hutter |
| 2022 | Switch to Generalize: Domain-Switch Learning for Cross-Domain Few-Shot Classification. Zhengdong Hu, Yifan Sun, Yi Yang |
| 2022 | Symbolic Learning to Optimize: Towards Interpretability and Scalability. Wenqing Zheng, Tianlong Chen, Ting-Kuei Hu, Zhangyang Wang |
| 2022 | Synchromesh: Reliable Code Generation from Pre-trained Language Models. Gabriel Poesia, Alex Polozov, Vu Le, Ashish Tiwari, Gustavo Soares, Christopher Meek, Sumit Gulwani |
| 2022 | T-WaveNet: A Tree-Structured Wavelet Neural Network for Time Series Signal Analysis. Minhao Liu, Ailing Zeng, Qiuxia Lai, Ruiyuan Gao, Min Li, Jing Qin, Qiang Xu |
| 2022 | TAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series Forecasting. Yuzhou Chen, Ignacio Segovia-Dominguez, Baris Coskunuzer, Yulia R. Gel |
| 2022 | TAPEX: Table Pre-training via Learning a Neural SQL Executor. Qian Liu, Bei Chen, Jiaqi Guo, Morteza Ziyadi, Zeqi Lin, Weizhu Chen, Jian-Guang Lou |
| 2022 | TAda! Temporally-Adaptive Convolutions for Video Understanding. Ziyuan Huang, Shiwei Zhang, Liang Pan, Zhiwu Qing, Mingqian Tang, Ziwei Liu, Marcelo H. Ang Jr. |
| 2022 | THOMAS: Trajectory Heatmap Output with learned Multi-Agent Sampling. Thomas Gilles, Stefano Sabatini, Dzmitry Tsishkou, Bogdan Stanciulescu, Fabien Moutarde |
| 2022 | TPU-GAN: Learning temporal coherence from dynamic point cloud sequences. Zijie Li, Tianqin Li, Amir Barati Farimani |
| 2022 | TRAIL: Near-Optimal Imitation Learning with Suboptimal Data. Mengjiao Yang, Sergey Levine, Ofir Nachum |
| 2022 | TRGP: Trust Region Gradient Projection for Continual Learning. Sen Lin, Li Yang, Deliang Fan, Junshan Zhang |
| 2022 | Tackling the Generative Learning Trilemma with Denoising Diffusion GANs. Zhisheng Xiao, Karsten Kreis, Arash Vahdat |
| 2022 | Taming Sparsely Activated Transformer with Stochastic Experts. Simiao Zuo, Xiaodong Liu, Jian Jiao, Young Jin Kim, Hany Hassan, Ruofei Zhang, Jianfeng Gao, Tuo Zhao |
| 2022 | Target-Side Input Augmentation for Sequence to Sequence Generation. Shufang Xie, Ang Lv, Yingce Xia, Lijun Wu, Tao Qin, Tie-Yan Liu, Rui Yan |
| 2022 | Task Affinity with Maximum Bipartite Matching in Few-Shot Learning. Cat Phuoc Le, Juncheng Dong, Mohammadreza Soltani, Vahid Tarokh |
| 2022 | Task Relatedness-Based Generalization Bounds for Meta Learning. Jiechao Guan, Zhiwu Lu |
| 2022 | Task-Induced Representation Learning. Jun Yamada, Karl Pertsch, Anisha Gunjal, Joseph J. Lim |
| 2022 | Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification. Bing Su, Ji-Rong Wen |
| 2022 | Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting. Shikuang Deng, Yuhang Li, Shanghang Zhang, Shi Gu |
| 2022 | The Boltzmann Policy Distribution: Accounting for Systematic Suboptimality in Human Models. Cassidy Laidlaw, Anca D. Dragan |
| 2022 | The Close Relationship Between Contrastive Learning and Meta-Learning. Renkun Ni, Manli Shu, Hossein Souri, Micah Goldblum, Tom Goldstein |
| 2022 | The Convex Geometry of Backpropagation: Neural Network Gradient Flows Converge to Extreme Points of the Dual Convex Program. Yifei Wang, Mert Pilanci |
| 2022 | The Effects of Invertibility on the Representational Complexity of Encoders in Variational Autoencoders. Divyansh Pareek, Andrej Risteski |
| 2022 | The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models. Alexander Pan, Kush Bhatia, Jacob Steinhardt |
| 2022 | The Efficiency Misnomer. Mostafa Dehghani, Yi Tay, Anurag Arnab, Lucas Beyer, Ashish Vaswani |
| 2022 | The Evolution of Uncertainty of Learning in Games. Yun Kuen Cheung, Georgios Piliouras, Yixin Tao |
| 2022 | The Geometry of Memoryless Stochastic Policy Optimization in Infinite-Horizon POMDPs. Johannes Müller, Guido Montúfar |
| 2022 | The Hidden Convex Optimization Landscape of Regularized Two-Layer ReLU Networks: an Exact Characterization of Optimal Solutions. Yifei Wang, Jonathan Lacotte, Mert Pilanci |
| 2022 | The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design. Yoav Levine, Noam Wies, Daniel Jannai, Dan Navon, Yedid Hoshen, Amnon Shashua |
| 2022 | The Information Geometry of Unsupervised Reinforcement Learning. Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine |
| 2022 | The MultiBERTs: BERT Reproductions for Robustness Analysis. Thibault Sellam, Steve Yadlowsky, Ian Tenney, Jason Wei, Naomi Saphra, Alexander D'Amour, Tal Linzen, Jasmijn Bastings, Iulia Raluca Turc, Jacob Eisenstein, Dipanjan Das, Ellie Pavlick |
| 2022 | The Neural Data Router: Adaptive Control Flow in Transformers Improves Systematic Generalization. Róbert Csordás, Kazuki Irie, Jürgen Schmidhuber |
| 2022 | The Rich Get Richer: Disparate Impact of Semi-Supervised Learning. Zhaowei Zhu, Tianyi Luo, Yang Liu |
| 2022 | The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks. Rahim Entezari, Hanie Sedghi, Olga Saukh, Behnam Neyshabur |
| 2022 | The Role of Pretrained Representations for the OOD Generalization of RL Agents. Frederik Träuble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer |
| 2022 | The Spectral Bias of Polynomial Neural Networks. Moulik Choraria, Leello Tadesse Dadi, Grigorios Chrysos, Julien Mairal, Volkan Cevher |
| 2022 | The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022 |
| 2022 | The Three Stages of Learning Dynamics in High-dimensional Kernel Methods. Nikhil Ghosh, Song Mei, Bin Yu |
| 2022 | The Uncanny Similarity of Recurrence and Depth. Avi Schwarzschild, Arjun Gupta, Amin Ghiasi, Micah Goldblum, Tom Goldstein |
| 2022 | The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy |
| 2022 | Tighter Sparse Approximation Bounds for ReLU Neural Networks. Carles Domingo-Enrich, Youssef Mroueh |
| 2022 | ToM2C: Target-oriented Multi-agent Communication and Cooperation with Theory of Mind. Yuanfei Wang, Fangwei Zhong, Jing Xu, Yizhou Wang |
| 2022 | Top-N: Equivariant Set and Graph Generation without Exchangeability. Clément Vignac, Pascal Frossard |
| 2022 | Top-label calibration and multiclass-to-binary reductions. Chirag Gupta, Aaditya Ramdas |
| 2022 | Topological Experience Replay. Zhang-Wei Hong, Tao Chen, Yen-Chen Lin, Joni Pajarinen, Pulkit Agrawal |
| 2022 | Topological Graph Neural Networks. Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt |
| 2022 | Topologically Regularized Data Embeddings. Robin Vandaele, Bo Kang, Jefrey Lijffijt, Tijl De Bie, Yvan Saeys |
| 2022 | Toward Efficient Low-Precision Training: Data Format Optimization and Hysteresis Quantization. Sunwoo Lee, Jeongwoo Park, Dongsuk Jeon |
| 2022 | Toward Faithful Case-based Reasoning through Learning Prototypes in a Nearest Neighbor-friendly Space. Seyed Omid Davoudi, Majid Komeili |
| 2022 | Towards Better Understanding and Better Generalization of Low-shot Classification in Histology Images with Contrastive Learning. Jiawei Yang, Hanbo Chen, Jiangpeng Yan, Xiaoyu Chen, Jianhua Yao |
| 2022 | Towards Building A Group-based Unsupervised Representation Disentanglement Framework. Tao Yang, Xuanchi Ren, Yuwang Wang, Wenjun Zeng, Nanning Zheng |
| 2022 | Towards Continual Knowledge Learning of Language Models. Joel Jang, Seonghyeon Ye, Sohee Yang, Joongbo Shin, Janghoon Han, Gyeonghun Kim, Stanley Jungkyu Choi, Minjoon Seo |
| 2022 | Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective. Wei Huang, Yayong Li, Weitao Du, Richard Y. D. Xu, Jie Yin, Ling Chen, Miao Zhang |
| 2022 | Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality. Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, Tie-Yan Liu |
| 2022 | Towards Empirical Sandwich Bounds on the Rate-Distortion Function. Yibo Yang, Stephan Mandt |
| 2022 | Towards Evaluating the Robustness of Neural Networks Learned by Transduction. Jiefeng Chen, Xi Wu, Yang Guo, Yingyu Liang, Somesh Jha |
| 2022 | Towards General Function Approximation in Zero-Sum Markov Games. Baihe Huang, Jason D. Lee, Zhaoran Wang, Zhuoran Yang |
| 2022 | Towards Model Agnostic Federated Learning Using Knowledge Distillation. Andrei Afonin, Sai Praneeth Karimireddy |
| 2022 | Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations. Anuroop Sriram, Abhishek Das, Brandon M. Wood, Siddharth Goyal, C. Lawrence Zitnick |
| 2022 | Towards Understanding Generalization via Decomposing Excess Risk Dynamics. Jiaye Teng, Jianhao Ma, Yang Yuan |
| 2022 | Towards Understanding the Data Dependency of Mixup-style Training. Muthu Chidambaram, Xiang Wang, Yuzheng Hu, Chenwei Wu, Rong Ge |
| 2022 | Towards Understanding the Robustness Against Evasion Attack on Categorical Data. Hongyan Bao, Yufei Han, Yujun Zhou, Yun Shen, Xiangliang Zhang |
| 2022 | Towards a Unified View of Parameter-Efficient Transfer Learning. Junxian He, Chunting Zhou, Xuezhe Ma, Taylor Berg-Kirkpatrick, Graham Neubig |
| 2022 | Tracking the risk of a deployed model and detecting harmful distribution shifts. Aleksandr Podkopaev, Aaditya Ramdas |
| 2022 | Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation. Ofir Press, Noah A. Smith, Mike Lewis |
| 2022 | Training Data Generating Networks: Shape Reconstruction via Bi-level Optimization. Biao Zhang, Peter Wonka |
| 2022 | Training Structured Neural Networks Through Manifold Identification and Variance Reduction. Zih-Syuan Huang, Ching-pei Lee |
| 2022 | Training Transition Policies via Distribution Matching for Complex Tasks. Ju-Seung Byun, Andrew Perrault |
| 2022 | Training invariances and the low-rank phenomenon: beyond linear networks. Thien Le, Stefanie Jegelka |
| 2022 | Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations. Fangyu Liu, Yunlong Jiao, Jordan Massiah, Emine Yilmaz, Serhii Havrylov |
| 2022 | Transfer RL across Observation Feature Spaces via Model-Based Regularization. Yanchao Sun, Ruijie Zheng, Xiyao Wang, Andrew E. Cohen, Furong Huang |
| 2022 | Transferable Adversarial Attack based on Integrated Gradients. Yi Huang, Adams Wai-Kin Kong |
| 2022 | Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design. Ye Yuan, Yuda Song, Zhengyi Luo, Wen Sun, Kris M. Kitani |
| 2022 | Transformer Embeddings of Irregularly Spaced Events and Their Participants. Hongyuan Mei, Chenghao Yang, Jason Eisner |
| 2022 | Transformer-based Transform Coding. Yinhao Zhu, Yang Yang, Taco Cohen |
| 2022 | Transformers Can Do Bayesian Inference. Samuel Müller, Noah Hollmann, Sebastian Pineda-Arango, Josif Grabocka, Frank Hutter |
| 2022 | Transition to Linearity of Wide Neural Networks is an Emerging Property of Assembling Weak Models. Chaoyue Liu, Libin Zhu, Mikhail Belkin |
| 2022 | Triangle and Four Cycle Counting with Predictions in Graph Streams. Justin Y. Chen, Talya Eden, Piotr Indyk, Honghao Lin, Shyam Narayanan, Ronitt Rubinfeld, Sandeep Silwal, Tal Wagner, David P. Woodruff, Michael Zhang |
| 2022 | Trigger Hunting with a Topological Prior for Trojan Detection. Xiaoling Hu, Xiao Lin, Michael Cogswell, Yi Yao, Susmit Jha, Chao Chen |
| 2022 | Trivial or Impossible --- dichotomous data difficulty masks model differences (on ImageNet and beyond). Kristof Meding, Luca M. Schulze Buschoff, Robert Geirhos, Felix A. Wichmann |
| 2022 | Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning. Jakub Grudzien Kuba, Ruiqing Chen, Muning Wen, Ying Wen, Fanglei Sun, Jun Wang, Yaodong Yang |
| 2022 | Tuformer: Data-driven Design of Transformers for Improved Generalization or Efficiency. Xiaoyu Liu, Jiahao Su, Furong Huang |
| 2022 | Uncertainty Modeling for Out-of-Distribution Generalization. Xiaotong Li, Yongxing Dai, Yixiao Ge, Jun Liu, Ying Shan, Lingyu Duan |
| 2022 | Understanding Dimensional Collapse in Contrastive Self-supervised Learning. Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian |
| 2022 | Understanding Domain Randomization for Sim-to-real Transfer. Xiaoyu Chen, Jiachen Hu, Chi Jin, Lihong Li, Liwei Wang |
| 2022 | Understanding Intrinsic Robustness Using Label Uncertainty. Xiao Zhang, David E. Evans |
| 2022 | Understanding Latent Correlation-Based Multiview Learning and Self-Supervision: An Identifiability Perspective. Qi Lyu, Xiao Fu, Weiran Wang, Songtao Lu |
| 2022 | Understanding and Improving Graph Injection Attack by Promoting Unnoticeability. Yongqiang Chen, Han Yang, Yonggang Zhang, Kaili Ma, Tongliang Liu, Bo Han, James Cheng |
| 2022 | Understanding and Leveraging Overparameterization in Recursive Value Estimation. Chenjun Xiao, Bo Dai, Jincheng Mei, Oscar A. Ramirez, Ramki Gummadi, Chris Harris, Dale Schuurmans |
| 2022 | Understanding and Preventing Capacity Loss in Reinforcement Learning. Clare Lyle, Mark Rowland, Will Dabney |
| 2022 | Understanding approximate and unrolled dictionary learning for pattern recovery. Benoît Malézieux, Thomas Moreau, Matthieu Kowalski |
| 2022 | Understanding over-squashing and bottlenecks on graphs via curvature. Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein |
| 2022 | Understanding the Role of Self Attention for Efficient Speech Recognition. Kyuhong Shim, Jungwook Choi, Wonyong Sung |
| 2022 | Understanding the Variance Collapse of SVGD in High Dimensions. Jimmy Ba, Murat A. Erdogdu, Marzyeh Ghassemi, Shengyang Sun, Taiji Suzuki, Denny Wu, Tianzong Zhang |
| 2022 | UniFormer: Unified Transformer for Efficient Spatial-Temporal Representation Learning. Kunchang Li, Yali Wang, Peng Gao, Guanglu Song, Yu Liu, Hongsheng Li, Yu Qiao |
| 2022 | Unified Visual Transformer Compression. Shixing Yu, Tianlong Chen, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Liu, Zhangyang Wang |
| 2022 | Unifying Likelihood-free Inference with Black-box Optimization and Beyond. Dinghuai Zhang, Jie Fu, Yoshua Bengio, Aaron C. Courville |
| 2022 | Universal Approximation Under Constraints is Possible with Transformers. Anastasis Kratsios, Behnoosh Zamanlooy, Tianlin Liu, Ivan Dokmanic |
| 2022 | Universalizing Weak Supervision. Changho Shin, Winfred Li, Harit Vishwakarma, Nicholas Carl Roberts, Frederic Sala |
| 2022 | Unraveling Model-Agnostic Meta-Learning via The Adaptation Learning Rate. Yingtian Zou, Fusheng Liu, Qianxiao Li |
| 2022 | Unrolling PALM for Sparse Semi-Blind Source Separation. Mohammad Fahes, Christophe Kervazo, Jérôme Bobin, Florence Tupin |
| 2022 | Unsupervised Discovery of Object Radiance Fields. Hong-Xing Yu, Leonidas J. Guibas, Jiajun Wu |
| 2022 | Unsupervised Disentanglement with Tensor Product Representations on the Torus. Michael Rotman, Amit Dekel, Shir Gur, Yaron Oz, Lior Wolf |
| 2022 | Unsupervised Learning of Full-Waveform Inversion: Connecting CNN and Partial Differential Equation in a Loop. Peng Jin, Xitong Zhang, Yinpeng Chen, Sharon Xiaolei Huang, Zicheng Liu, Youzuo Lin |
| 2022 | Unsupervised Semantic Segmentation by Distilling Feature Correspondences. Mark Hamilton, Zhoutong Zhang, Bharath Hariharan, Noah Snavely, William T. Freeman |
| 2022 | Unsupervised Vision-Language Grammar Induction with Shared Structure Modeling. Bo Wan, Wenjuan Han, Zilong Zheng, Tinne Tuytelaars |
| 2022 | Using Graph Representation Learning with Schema Encoders to Measure the Severity of Depressive Symptoms. Simin Hong, Anthony G. Cohn, David Crossland Hogg |
| 2022 | VAE Approximation Error: ELBO and Exponential Families. Alexander Shekhovtsov, Dmitrij Schlesinger, Boris Flach |
| 2022 | VAT-Mart: Learning Visual Action Trajectory Proposals for Manipulating 3D ARTiculated Objects. Ruihai Wu, Yan Zhao, Kaichun Mo, Zizheng Guo, Yian Wang, Tianhao Wu, Qingnan Fan, Xuelin Chen, Leonidas J. Guibas, Hao Dong |
| 2022 | VC dimension of partially quantized neural networks in the overparametrized regime. Yutong Wang, Clayton Scott |
| 2022 | VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning. Adrien Bardes, Jean Ponce, Yann LeCun |
| 2022 | VOS: Learning What You Don't Know by Virtual Outlier Synthesis. Xuefeng Du, Zhaoning Wang, Mu Cai, Yixuan Li |
| 2022 | Value Function Spaces: Skill-Centric State Abstractions for Long-Horizon Reasoning. Dhruv Shah, Peng Xu, Yao Lu, Ted Xiao, Alexander Toshev, Sergey Levine, Brian Ichter |
| 2022 | Value Gradient weighted Model-Based Reinforcement Learning. Claas Voelcker, Victor Liao, Animesh Garg, Amir-massoud Farahmand |
| 2022 | Variational Inference for Discriminative Learning with Generative Modeling of Feature Incompletion. Kohei Miyaguchi, Takayuki Katsuki, Akira Koseki, Toshiya Iwamori |
| 2022 | Variational Neural Cellular Automata. Rasmus Berg Palm, Miguel González Duque, Shyam Sudhakaran, Sebastian Risi |
| 2022 | Variational Predictive Routing with Nested Subjective Timescales. Alexey Zakharov, Qinghai Guo, Zafeirios Fountas |
| 2022 | Variational autoencoders in the presence of low-dimensional data: landscape and implicit bias. Frederic Koehler, Viraj Mehta, Chenghui Zhou, Andrej Risteski |
| 2022 | Variational methods for simulation-based inference. Manuel Glöckler, Michael Deistler, Jakob H. Macke |
| 2022 | Variational oracle guiding for reinforcement learning. Dongqi Han, Tadashi Kozuno, Xufang Luo, Zhao-Yun Chen, Kenji Doya, Yuqing Yang, Dongsheng Li |
| 2022 | Vector-quantized Image Modeling with Improved VQGAN. Jiahui Yu, Xin Li, Jing Yu Koh, Han Zhang, Ruoming Pang, James Qin, Alexander Ku, Yuanzhong Xu, Jason Baldridge, Yonghui Wu |
| 2022 | ViDT: An Efficient and Effective Fully Transformer-based Object Detector. Hwanjun Song, Deqing Sun, Sanghyuk Chun, Varun Jampani, Dongyoon Han, Byeongho Heo, Wonjae Kim, Ming-Hsuan Yang |
| 2022 | ViTGAN: Training GANs with Vision Transformers. Kwonjoon Lee, Huiwen Chang, Lu Jiang, Han Zhang, Zhuowen Tu, Ce Liu |
| 2022 | Vision-Based Manipulators Need to Also See from Their Hands. Kyle Hsu, Moo Jin Kim, Rafael Rafailov, Jiajun Wu, Chelsea Finn |
| 2022 | Visual Correspondence Hallucination. Hugo Germain, Vincent Lepetit, Guillaume Bourmaud |
| 2022 | Visual Representation Learning Does Not Generalize Strongly Within the Same Domain. Lukas Schott, Julius von Kügelgen, Frederik Träuble, Peter Vincent Gehler, Chris Russell, Matthias Bethge, Bernhard Schölkopf, Francesco Locatello, Wieland Brendel |
| 2022 | Visual Representation Learning over Latent Domains. Lucas Deecke, Timothy M. Hospedales, Hakan Bilen |
| 2022 | Visual hyperacuity with moving sensor and recurrent neural computations. Alexander Rivkind, Or Ram, Eldad Assa, Michael Kreiserman, Ehud Ahissar |
| 2022 | Vitruvion: A Generative Model of Parametric CAD Sketches. Ari Seff, Wenda Zhou, Nick Richardson, Ryan P. Adams |
| 2022 | W-CTC: a Connectionist Temporal Classification Loss with Wild Cards. Xingyu Cai, Jiahong Yuan, Yuchen Bian, Guangxu Xun, Jiaji Huang, Kenneth Church |
| 2022 | WeakM3D: Towards Weakly Supervised Monocular 3D Object Detection. Liang Peng, Senbo Yan, Boxi Wu, Zheng Yang, Xiaofei He, Deng Cai |
| 2022 | Weighted Training for Cross-Task Learning. Shuxiao Chen, Koby Crammer, Hangfeng He, Dan Roth, Weijie J. Su |
| 2022 | What Do We Mean by Generalization in Federated Learning? Honglin Yuan, Warren Richard Morningstar, Lin Ning, Karan Singhal |
| 2022 | What Happens after SGD Reaches Zero Loss? --A Mathematical Framework. Zhiyuan Li, Tianhao Wang, Sanjeev Arora |
| 2022 | What Makes Better Augmentation Strategies? Augment Difficult but Not too Different. Jaehyung Kim, Dongyeop Kang, Sungsoo Ahn, Jinwoo Shin |
| 2022 | What's Wrong with Deep Learning in Tree Search for Combinatorial Optimization. Maximilian Böther, Otto Kißig, Martin Taraz, Sarel Cohen, Karen Seidel, Tobias Friedrich |
| 2022 | When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently? Ziang Song, Song Mei, Yu Bai |
| 2022 | When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations. Xiangning Chen, Cho-Jui Hsieh, Boqing Gong |
| 2022 | When should agents explore? Miruna Pislar, David Szepesvari, Georg Ostrovski, Diana L. Borsa, Tom Schaul |
| 2022 | When, Why, and Which Pretrained GANs Are Useful? Timofey Grigoryev, Andrey Voynov, Artem Babenko |
| 2022 | Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective. Luca Scimeca, Seong Joon Oh, Sanghyuk Chun, Michael Poli, Sangdoo Yun |
| 2022 | Who Is Your Right Mixup Partner in Positive and Unlabeled Learning. Changchun Li, Ximing Li, Lei Feng, Jihong Ouyang |
| 2022 | Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL. Yanchao Sun, Ruijie Zheng, Yongyuan Liang, Furong Huang |
| 2022 | Why Propagate Alone? Parallel Use of Labels and Features on Graphs. Yangkun Wang, Jiarui Jin, Weinan Zhang, Yongyi Yang, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf |
| 2022 | Wiring Up Vision: Minimizing Supervised Synaptic Updates Needed to Produce a Primate Ventral Stream. Franziska Geiger, Martin Schrimpf, Tiago Marques, James J. DiCarlo |
| 2022 | Wisdom of Committees: An Overlooked Approach To Faster and More Accurate Models. Xiaofang Wang, Dan Kondratyuk, Eric Christiansen, Kris M. Kitani, Yair Movshovitz-Attias, Elad Eban |
| 2022 | Wish you were here: Hindsight Goal Selection for long-horizon dexterous manipulation. Todor Davchev, Oleg Olegovich Sushkov, Jean-Baptiste Regli, Stefan Schaal, Yusuf Aytar, Markus Wulfmeier, Jon Scholz |
| 2022 | X-model: Improving Data Efficiency in Deep Learning with A Minimax Model. Ximei Wang, Xinyang Chen, Jianmin Wang, Mingsheng Long |
| 2022 | You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction. Osama Makansi, Julius von Kügelgen, Francesco Locatello, Peter Vincent Gehler, Dominik Janzing, Thomas Brox, Bernhard Schölkopf |
| 2022 | You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks. Eli Chien, Chao Pan, Jianhao Peng, Olgica Milenkovic |
| 2022 | Zero Pixel Directional Boundary by Vector Transform. Edoardo Mello Rella, Ajad Chhatkuli, Yun Liu, Ender Konukoglu, Luc Van Gool |
| 2022 | Zero-CL: Instance and Feature decorrelation for negative-free symmetric contrastive learning. Shaofeng Zhang, Feng Zhu, Junchi Yan, Rui Zhao, Xiaokang Yang |
| 2022 | Zero-Shot Self-Supervised Learning for MRI Reconstruction. Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Mehmet Akçakaya |
| 2022 | ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity. Xinchi Qiu, Javier Fernández-Marqués, Pedro P. B. de Gusmao, Yan Gao, Titouan Parcollet, Nicholas Donald Lane |
| 2022 | cosFormer: Rethinking Softmax In Attention. Zhen Qin, Weixuan Sun, Hui Deng, Dongxu Li, Yunshen Wei, Baohong Lv, Junjie Yan, Lingpeng Kong, Yiran Zhong |
| 2022 | iFlood: A Stable and Effective Regularizer. Yuexiang Xie, Zhen Wang, Yaliang Li, Ce Zhang, Jingren Zhou, Bolin Ding |
| 2022 | iLQR-VAE : control-based learning of input-driven dynamics with applications to neural data. Marine Schimel, Ta-Chu Kao, Kristopher T. Jensen, Guillaume Hennequin |
| 2022 | miniF2F: a cross-system benchmark for formal Olympiad-level mathematics. Kunhao Zheng, Jesse Michael Han, Stanislas Polu |
| 2022 | switch-GLAT: Multilingual Parallel Machine Translation Via Code-Switch Decoder. Zhenqiao Song, Hao Zhou, Lihua Qian, Jingjing Xu, Shanbo Cheng, Mingxuan Wang, Lei Li |