| 2022 | A causal bandit approach to learning good atomic interventions in presence of unobserved confounders. Aurghya Maiti, Vineet Nair, Gaurav Sinha |
| 2022 | A competitive analysis of online failure-aware assignment. Mengjing Chen, Pingzhong Tang, Zihe Wang, Shenke Xiao, Xiwang Yang |
| 2022 | A free lunch from the noise: Provable and practical exploration for representation learning. Tongzheng Ren, Tianjun Zhang, Csaba Szepesvári, Bo Dai |
| 2022 | A geometric method for improved uncertainty estimation in real-time. Gabriella Chouraqui, Liron Cohen, Gil Einziger, Liel Leman |
| 2022 | A label efficient two-sample test. Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha |
| 2022 | A mutually exciting latent space Hawkes process model for continuous-time networks. Zhipeng Huang, Hadeel Soliman, Subhadeep Paul, Kevin S. Xu |
| 2022 | A new constructive criterion for Markov equivalence of MAGs. Marcel Wienöbst, Max Bannach, Maciej Liskiewicz |
| 2022 | A robustness test for estimating total effects with covariate adjustment. Zehao Su, Leonard Henckel |
| 2022 | AND/OR branch-and-bound for computational protein design optimizing K. Bobak Pezeshki, Radu Marinescu, Alexander Ihler, Rina Dechter |
| 2022 | AUTM flow: atomic unrestricted time machine for monotonic normalizing flows. Difeng Cai, Yuliang Ji, Huan He, Qiang Ye, Yuanzhe Xi |
| 2022 | Accelerating training of batch normalization: A manifold perspective. Mingyang Yi |
| 2022 | Active approximately metric-fair learning. Yiting Cao, Chao Lan |
| 2022 | Active learning with label comparisons. Gal Yona, Shay Moran, Gal Elidan, Amir Globerson |
| 2022 | AdaCat: Adaptive categorical discretization for autoregressive models. Qiyang Li, Ajay Jain, Pieter Abbeel |
| 2022 | Addressing token uniformity in transformers via singular value transformation. Hanqi Yan, Lin Gui, Wenjie Li, Yulan He |
| 2022 | An explore-then-commit algorithm for submodular maximization under full-bandit feedback. Guanyu Nie, Mridul Agarwal, Abhishek Kumar Umrawal, Vaneet Aggarwal, Christopher John Quinn |
| 2022 | Asymmetric DQN for partially observable reinforcement learning. Andrea Baisero, Brett Daley, Christopher Amato |
| 2022 | Asymptotic optimality for active learning processes. Xueying Zhan, Yaowei Wang, Antoni B. Chan |
| 2022 | Attribution of predictive uncertainties in classification models. Iker Perez, Piotr Skalski, Alec Barns-Graham, Jason Wong, David Sutton |
| 2022 | Balancing adaptability and non-exploitability in repeated games. Anthony DiGiovanni, Ambuj Tewari |
| 2022 | Balancing utility and scalability in metric differential privacy. Jacob Imola, Shiva Prasad Kasiviswanathan, Stephen White, Abhinav Aggarwal, Nathanael Teissier |
| 2022 | Bayesian federated estimation of causal effects from observational data. Thanh Vinh Vo, Young Lee, Trong Nghia Hoang, Tze-Yun Leong |
| 2022 | Bayesian quantile and expectile optimisation. Victor Picheny, Henry B. Moss, Léeonard Torossian, Nicolas Durrande |
| 2022 | Bayesian spillover graphs for dynamic networks. Grace Deng, David S. Matteson |
| 2022 | Bayesian structure learning with generative flow networks. Tristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio |
| 2022 | Bias aware probabilistic Boolean matrix factorization. Changlin Wan, Pengtao Dang, Tong Zhao, Yong Zang, Chi Zhang, Sha Cao |
| 2022 | Binary independent component analysis: a non-stationarity-based approach. Antti Hyttinen, Vitória Barin Pacela, Aapo Hyvärinen |
| 2022 | Byzantine-tolerant distributed multiclass sparse linear discriminant analysis. Yajie Bao, Weidong Liu, Xiaojun Mao, Weijia Xiong |
| 2022 | CIGMO: Categorical invariant representations in a deep generative framework. Haruo Hosoya |
| 2022 | Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift. Ananya Kumar, Tengyu Ma, Percy Liang, Aditi Raghunathan |
| 2022 | Can mean field control (mfc) approximate cooperative multi agent reinforcement learning (marl) with non-uniform interaction? Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri |
| 2022 | Capturing actionable dynamics with structured latent ordinary differential equations. Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao |
| 2022 | Case-based off-policy evaluation using prototype learning. Anton Matsson, Fredrik D. Johansson |
| 2022 | Causal discovery under a confounder blanket. David S. Watson, Ricardo Silva |
| 2022 | Causal discovery with heterogeneous observational data. Fangting Zhou, Kejun He, Yang Ni |
| 2022 | Causal forecasting: generalization bounds for autoregressive models. Leena Chennuru Vankadara, Philipp Michael Faller, Michaela Hardt, Lenon Minorics, Debarghya Ghoshdastidar, Dominik Janzing |
| 2022 | Causal inference with treatment measurement error: a nonparametric instrumental variable approach. Yuchen Zhu, Limor Gultchin, Arthur Gretton, Matt J. Kusner, Ricardo Silva |
| 2022 | Clustering a union of linear subspaces via matrix factorization and innovation search. Mostafa Rahmani |
| 2022 | CoSPA: An improved masked language model with copy mechanism for Chinese spelling correction. Shoujian Yang, Lian Yu |
| 2022 | Combating the instability of mutual information-based losses via regularization. Kwanghee Choi, Siyeong Lee |
| 2022 | Combinatorial Bayesian optimization with random mapping functions to convex polytopes. Jungtaek Kim, Seungjin Choi, Minsu Cho |
| 2022 | Conditional simulation using diffusion Schrödinger bridges. Yuyang Shi, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet |
| 2022 | Contrastive latent variable models for neural text generation. Zhiyang Teng, Chenhua Chen, Yan Zhang, Yue Zhang |
| 2022 | Convergence Analysis of Linear Coupling with Inexact Proximal Operator. Qiang Zhou, Sinno Jialin Pan |
| 2022 | CounteRGAN: Generating counterfactuals for real-time recourse and interpretability using residual GANs. Daniel Nemirovsky, Nicolas Thiebaut, Ye Xu, Abhishek Gupta |
| 2022 | Counterfactual inference of second Opinions. Nina L. Corvelo Benz, Manuel Gomez Rodriguez |
| 2022 | Cross-domain adaptive transfer reinforcement learning based on state-action correspondence. Heng You, Tianpei Yang, Yan Zheng, Jianye Hao, Matthew E. Taylor |
| 2022 | Cycle class consistency with distributional optimal transport and knowledge distillation for unsupervised domain adaptation. Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran, Dinh Q. Phung |
| 2022 | Cyclic test time augmentation with entropy weight method. Sewhan Chun, Jae Young Lee, Junmo Kim |
| 2022 | Data augmentation in Bayesian neural networks and the cold posterior effect. Seth Nabarro, Stoil Ganev, Adrià Garriga-Alonso, Vincent Fortuin, Mark van der Wilk, Laurence Aitchison |
| 2022 | Data dependent randomized smoothing. Motasem Alfarra, Adel Bibi, Philip H. S. Torr, Bernard Ghanem |
| 2022 | Data poisoning attacks on off-policy policy evaluation methods. Elita A. Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju |
| 2022 | Data sampling affects the complexity of online SGD over dependent data. Shaocong Ma, Ziyi Chen, Yi Zhou, Kaiyi Ji, Yingbin Liang |
| 2022 | Decision-theoretic planning with communication in open multiagent systems. Anirudh Kakarlapudi, Gayathri Anil, Adam Eck, Prashant Doshi, Leen-Kiat Soh |
| 2022 | Deep Dirichlet process mixture models. Naiqi Li, Wenjie Li, Yong Jiang, Shu-Tao Xia |
| 2022 | Detecting textual adversarial examples through randomized substitution and vote. Xiaosen Wang, Yifeng Xiong, Kun He |
| 2022 | Deterministic policy gradient: Convergence analysis. Huaqing Xiong, Tengyu Xu, Lin Zhao, Yingbin Liang, Wei Zhang |
| 2022 | Differentially private SGDA for minimax problems. Zhenhuan Yang, Shu Hu, Yunwen Lei, Kush R. Varshney, Siwei Lyu, Yiming Ying |
| 2022 | Differentially private multi-party data release for linear regression. Ruihan Wu, Xin Yang, Yuanshun Yao, Jiankai Sun, Tianyi Liu, Kilian Q. Weinberger, Chong Wang |
| 2022 | Dimension reduction for high-dimensional small counts with KL divergence. Yurong Ling, Jing-Hao Xue |
| 2022 | Discovery of extended summary graphs in time series. Charles K. Assaad, Emilie Devijver, Éric Gaussier |
| 2022 | Distributed adversarial training to robustify deep neural networks at scale. Gaoyuan Zhang, Songtao Lu, Yihua Zhang, Xiangyi Chen, Pin-Yu Chen, Quanfu Fan, Lee Martie, Lior Horesh, Mingyi Hong, Sijia Liu |
| 2022 | Do Bayesian variational autoencoders know what they don't know? Misha Glazunov, Apostolis Zarras |
| 2022 | Dynamic relocation in ridesharing via fixpoint construction. Ian A. Kash, Zhongkai Wen, Lenore D. Zuck |
| 2022 | Efficient and accurate top-k recovery from choice data. Duc Nguyen |
| 2022 | Efficient and transferable adversarial examples from bayesian neural networks. Martin Gubri, Maxime Cordy, Mike Papadakis, Yves Le Traon, Koushik Sen |
| 2022 | Efficient inference for dynamic topic modeling with large vocabularies. Federico Tomasi, Mounia Lalmas, Zhenwen Dai |
| 2022 | Efficient learning of sparse and decomposable PDEs using random projection. Md. Nasim, Xinghang Zhang, Anter El-Azab, Yexiang Xue |
| 2022 | Efficient resource allocation with fairness constraints in restless multi-armed bandits. Dexun Li, Pradeep Varakantham |
| 2022 | Empirical bayes approach to truth discovery problems. Tsviel Ben Shabat, Reshef Meir, David Azriel |
| 2022 | Enhanced adaptive optics control with image to image translation. Jeffrey Smith, Jesse Cranney, Charles Gretton, Damien Gratadour |
| 2022 | Equilibrium aggregation: encoding sets via optimization. Sergey Bartunov, Fabian B. Fuchs, Timothy P. Lillicrap |
| 2022 | Estimating transfer entropy under long ranged dependencies. Sahil Garg, Umang Gupta, Yu Chen, Syamantak Datta Gupta, Yeshaya Adler, Anderson Schneider, Yuriy Nevmyvaka |
| 2022 | Evaluating high-order predictive distributions in deep learning. Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Benjamin Van Roy |
| 2022 | Expectation programming: Adapting probabilistic programming systems to estimate expectations efficiently. Tim Reichelt, Adam Golinski, Luke Ong, Tom Rainforth |
| 2022 | Fast inference and transfer of compositional task structures for few-shot task generalization. Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Lyubing Qiang, Izzeddin Gur, Aleksandra Faust, Honglak Lee |
| 2022 | Fast predictive uncertainty for classification with Bayesian deep networks. Marius Hobbhahn, Agustinus Kristiadi, Philipp Hennig |
| 2022 | Faster non-convex federated learning via global and local momentum. Rudrajit Das, Anish Acharya, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu |
| 2022 | Feature learning and random features in standard finite-width convolutional neural networks: An empirical study. Maxim Samarin, Volker Roth, David Belius |
| 2022 | Feature selection for discovering distributional treatment effect modifiers. Yoichi Chikahara, Makoto Yamada, Hisashi Kashima |
| 2022 | Federated online clustering of bandits. Xutong Liu, Haoru Zhao, Tong Yu, Shuai Li, John C. S. Lui |
| 2022 | Fedvarp: Tackling the variance due to partial client participation in federated learning. Divyansh Jhunjhunwala, Pranay Sharma, Aushim Nagarkatti, Gauri Joshi |
| 2022 | Fine-Grained matching with multi-perspective similarity modeling for cross-modal retrieval. Xiumin Xie, Chuanwen Hou, Zhixin Li |
| 2022 | Finite-horizon equilibria for neuro-symbolic concurrent stochastic games. Rui Yan, Gabriel Santos, Xiaoming Duan, David Parker, Marta Kwiatkowska |
| 2022 | Fixing the Bethe approximation: How structural modifications in a graph improve belief propagation. Harald Leisenberger, Franz Pernkopf, Christian Knoll |
| 2022 | Forget-me-not! Contrastive critics for mitigating posterior collapse. Sachit Menon, David M. Blei, Carl Vondrick |
| 2022 | Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems. Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu |
| 2022 | GNN2GNN: Graph neural networks to generate neural networks. Andrea Agiollo, Andrea Omicini |
| 2022 | Generalized Bayesian quadrature with spectral kernels. Houston Warren, Rafael Oliveira, Fabio T. Ramos |
| 2022 | Generalizing off-policy learning under sample selection bias. Tobias Hatt, Daniel Tschernutter, Stefan Feuerriegel |
| 2022 | Greedy equivalence search in the presence of latent confounders. Tom Claassen, Ioan Gabriel Bucur |
| 2022 | Greedy modality selection via approximate submodular maximization. Runxiang Cheng, Gargi Balasubramaniam, Yifei He, Yao-Hung Hubert Tsai, Han Zhao |
| 2022 | Greedy relaxations of the sparsest permutation algorithm. Wai-Yin Lam, Bryan Andrews, Joseph D. Ramsey |
| 2022 | High-probability bounds for robust stochastic Frank-Wolfe algorithm. Tongyi Tang, Krishna Balasubramanian, Thomas Chun Man Lee |
| 2022 | Hitting times for continuous-time imprecise-Markov chains. Thomas Krak |
| 2022 | How unfair is private learning? Amartya Sanyal, Yaxi Hu, Fanny Yang |
| 2022 | Identifiability of sparse causal effects using instrumental variables. Niklas Pfister, Jonas Peters |
| 2022 | Identifying near-optimal decisions in linear-in-parameter bandit models with continuous decision sets. Sanjay P. Bhat, Chaitanya Amballa |
| 2022 | If you've trained one you've trained them all: inter-architecture similarity increases with robustness. Haydn Thomas Jones, Jacob M. Springer, Garrett T. Kenyon, Juston S. Moore |
| 2022 | Implicit kernel meta-learning using kernel integral forms. John Isak Texas Falk, Carlo Ciliberto, Massimiliano Pontil |
| 2022 | Improved feature importance computation for tree models based on the Banzhaf value. Adam Karczmarz, Tomasz P. Michalak, Anish Mukherjee, Piotr Sankowski, Piotr Wygocki |
| 2022 | Improving sign-random-projection via count sketch. Punit Pankaj Dubey, Bhisham Dev Verma, Rameshwar Pratap, Keegan Kang |
| 2022 | Individual fairness in feature-based pricing for monopoly markets. Shantanu Das, Swapnil Dhamal, Ganesh Ghalme, Shweta Jain, Sujit Gujar |
| 2022 | Inductive synthesis of finite-state controllers for POMDPs. Roman Andriushchenko, Milan Ceska, Sebastian Junges, Joost-Pieter Katoen |
| 2022 | Information design for multiple independent and self-interested defenders: Work less, pay off more. Chenghan Zhou, Andrew Spivey, Haifeng Xu, Thanh Hong Nguyen |
| 2022 | Information theoretic approach to detect collusion in multi-agent games. Trevor Bonjour, Vaneet Aggarwal, Bharat K. Bhargava |
| 2022 | Interpolating between sampling and variational inference with infinite stochastic mixtures. Richard D. Lange, Ari S. Benjamin, Ralf M. Haefner, Xaq Pitkow |
| 2022 | Intervention target estimation in the presence of latent variables. Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer |
| 2022 | Knowledge representation combining quaternion path integration and depth-wise atrous circular convolution. Xinyuan Chen, Zhongmei Zhou, Meichun Gao, Daya Shi, Mohd Nizam Husen |
| 2022 | Laplace approximated Gaussian process state-space models. Jakob Lindinger, Barbara Rakitsch, Christoph Lippert |
| 2022 | Learning a neural Pareto manifold extractor with constraints. Soumyajit Gupta, Gurpreet Singh, Raghu Bollapragada, Matthew Lease |
| 2022 | Learning binary multi-scale games on networks. Sixie Yu, P. Jeffrey Brantingham, Matthew Valasik, Yevgeniy Vorobeychik |
| 2022 | Learning explainable templated graphical models. Varun Embar, Sriram Srinivasan, Lise Getoor |
| 2022 | Learning functions on multiple sets using multi-set transformers. Kira A. Selby, Ahmad Rashid, Ivan Kobyzev, Mehdi Rezagholizadeh, Pascal Poupart |
| 2022 | Learning in Markov games: Can we exploit a general-sum opponent? Giorgia Ramponi, Marcello Restelli |
| 2022 | Learning invariant weights in neural networks. Tycho F. A. van der Ouderaa, Mark van der Wilk |
| 2022 | Learning large Bayesian networks with expert constraints. Vaidyanathan Peruvemba Ramaswamy, Stefan Szeider |
| 2022 | Learning linear non-Gaussian polytree models. Daniele Tramontano, Anthea Monod, Mathias Drton |
| 2022 | Learning soft interventions in complex equilibrium systems. Michel Besserve, Bernhard Schölkopf |
| 2022 | Learning sparse representations of preferences within Choquet expected utility theory. Margot Herin, Patrice Perny, Nataliya Sokolovska |
| 2022 | Lifting in multi-agent systems under uncertainty. Tanya Braun, Marcel Gehrke, Florian Lau, Ralf Möller |
| 2022 | Linearizing contextual bandits with latent state dynamics. Elliot Nelson, Debarun Bhattacharjya, Tian Gao, Miao Liu, Djallel Bouneffouf, Pascal Poupart |
| 2022 | Local calibration: metrics and recalibration. Rachel Luo, Aadyot Bhatnagar, Yu Bai, Shengjia Zhao, Huan Wang, Caiming Xiong, Silvio Savarese, Stefano Ermon, Edward Schmerling, Marco Pavone |
| 2022 | Low-precision arithmetic for fast Gaussian processes. Wesley J. Maddox, Andres Potapczynski, Andrew Gordon Wilson |
| 2022 | Marginal MAP estimation for inverse RL under occlusion with observer noise. Prasanth Sengadu Suresh, Prashant Doshi |
| 2022 | Meta-learning without data via Wasserstein distributionally-robust model fusion. Zhenyi Wang, Xiaoyang Wang, Li Shen, Qiuling Suo, Kaiqiang Song, Dong Yu, Yan Shen, Mingchen Gao |
| 2022 | Mitigating statistical bias within differentially private synthetic data. Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes |
| 2022 | Modeling extremes with d-max-decreasing neural networks. Ali Hasan, Khalil Elkhalil, Yuting Ng, João M. Pereira, Sina Farsiu, Jose H. Blanchet, Vahid Tarokh |
| 2022 | Monotonicity regularization: Improved penalties and novel applications to disentangled representation learning and robust classification. Joao Monteiro, Mohamed Osama Ahmed, Hossein Hajimirsadeghi, Greg Mori |
| 2022 | Multi-objective Bayesian optimization over high-dimensional search spaces. Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy |
| 2022 | Multi-source domain adaptation via weighted joint distributions optimal transport. Rosanna Turrisi, Rémi Flamary, Alain Rakotomamonjy, Massimiliano Pontil |
| 2022 | Multi-winner approval voting goes epistemic. Tahar Allouche, Jérôme Lang, Florian Yger |
| 2022 | Multiclass classification for Hawkes processes. Christophe Denis, Charlotte Dion-Blanc, Laure Sansonnet |
| 2022 | Multistate analysis with infinite mixtures of Markov chains. Lucas Maystre, Tiffany Wu, Roberto Sanchis-Ojeda, Tony Jebara |
| 2022 | Mutation-driven follow the regularized leader for last-iterate convergence in zero-sum games. Kenshi Abe, Mitsuki Sakamoto, Atsushi Iwasaki |
| 2022 | Mutual information based Bayesian graph neural network for few-shot learning. Kaiyu Song, Kun Yue, Liang Duan, Mingze Yang, Angsheng Li |
| 2022 | Near-optimal Thompson sampling-based algorithms for differentially private stochastic bandits. Bingshan Hu, Nidhi Hegde |
| 2022 | Neural ensemble search via Bayesian sampling. Yao Shu, Yizhou Chen, Zhongxiang Dai, Bryan Kian Hsiang Low |
| 2022 | Neural-progressive hedging: Enforcing constraints in reinforcement learning with stochastic programming. Supriyo Ghosh, Laura Wynter, Shiau Hong Lim, Duc Thien Nguyen |
| 2022 | Neuro-symbolic entropy regularization. Kareem Ahmed, Eric Wang, Kai-Wei Chang, Guy Van den Broeck |
| 2022 | NeuroBE: Escalating neural network approximations of Bucket Elimination. Sakshi Agarwal, Kalev Kask, Alexander Ihler, Rina Dechter |
| 2022 | Noisy L0-sparse subspace clustering on dimensionality reduced data. Yingzhen Yang, Ping Li |
| 2022 | Non-parametric inference of relational dependence. Ragib Ahsan, Zahra Fatemi, David Arbour, Elena Zheleva |
| 2022 | Nonparametric exponential family graph embeddings for multiple representation learning. Chien Lu, Jaakko Peltonen, Timo Nummenmaa, Jyrki Nummenmaa |
| 2022 | Offline change detection under contamination. Sujay Bhatt, Guanhua Fang, Ping Li |
| 2022 | Offline policy optimization with eligible actions. Yao Liu, Yannis Flet-Berliac, Emma Brunskill |
| 2022 | Offline reinforcement learning under value and density-ratio realizability: The power of gaps. Jinglin Chen, Nan Jiang |
| 2022 | Offline stochastic shortest path: Learning, evaluation and towards optimality. Ming Yin, Wenjing Chen, Mengdi Wang, Yu-Xiang Wang |
| 2022 | On early extinction and the effect of travelling in the SIR model. Petra Berenbrink, Colin Cooper, Cristina Gava, David Kohan Marzagão, Frederik Mallmann-Trenn, Tomasz Radzik |
| 2022 | On provably robust meta-Bayesian optimization. Zhongxiang Dai, Yizhou Chen, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet |
| 2022 | On testability of the front-door model via Verma constraints. Rohit Bhattacharya, Razieh Nabi |
| 2022 | On the definition and computation of causal treewidth. Yizuo Chen, Adnan Darwiche |
| 2022 | On the effectiveness of adversarial training against common corruptions. Klim Kireev, Maksym Andriushchenko, Nicolas Flammarion |
| 2022 | On the inductive bias of neural networks for learning read-once DNFs. Ido Bronstein, Alon Brutzkus, Amir Globerson |
| 2022 | On-the-fly adaptation of patrolling strategies in changing environments. Tomás Brázdil, David Klaska, Antonín Kucera, Vít Musil, Petr Novotný, Vojtech Rehák |
| 2022 | Optimal control of partially observable Markov decision processes with finite linear temporal logic constraints. Krishna Chaitanya Kalagarla, Dhruva Kartik, Dongming Shen, Rahul Jain, Ashutosh Nayyar, Pierluigi Nuzzo |
| 2022 | Ordinal causal discovery. Yang Ni, Bani K. Mallick |
| 2022 | Orthogonal Gromov-Wasserstein discrepancy with efficient lower bound. Hongwei Jin, Zishun Yu, Xinhua Zhang |
| 2022 | PAC-Bayesian domain adaptation bounds for multiclass learners. Anthony Sicilia, Katherine Atwell, Malihe Alikhani, Seong Jae Hwang |
| 2022 | PDQ-Net: Deep probabilistic dual quaternion network for absolute pose regression on SE(3). Wenjie Li, Wasif Naeem, Jia Liu, Dequan Zheng, Wei Hao, Lijun Chen |
| 2022 | Pareto navigation gradient descent: a first-order algorithm for optimization in pareto set. Mao Ye, Qiang Liu |
| 2022 | Partial likelihood Thompson sampling. Han Wu, Stefan Wager |
| 2022 | Partially adaptive regularized multiple regression analysis for estimating linear causal effects. Hisayoshi Nanmo, Manabu Kuroki |
| 2022 | PathFlow: A normalizing flow generator that finds transition paths. Tianyi Liu, Weihao Gao, Zhirui Wang, Chong Wang |
| 2022 | Perturbation type categorization for multiple adversarial perturbation robustness. Pratyush Maini, Xinyun Chen, Bo Li, Dawn Song |
| 2022 | Physics guided neural networks for spatio-temporal super-resolution of turbulent flows. Tianshu Bao, Shengyu Chen, Taylor T. Johnson, Peyman Givi, Shervin Sammak, Xiaowei Jia |
| 2022 | Predictive Whittle networks for time series. Zhongjie Yu, Fabrizio Ventola, Nils Thoma, Devendra Singh Dhami, Martin Mundt, Kristian Kersting |
| 2022 | Principle of relevant information for graph sparsification. Shujian Yu, Francesco Alesiani, Wenzhe Yin, Robert Jenssen, José C. Príncipe |
| 2022 | Privacy-aware compression for federated data analysis. Kamalika Chaudhuri, Chuan Guo, Mike Rabbat |
| 2022 | Probabilistic spatial transformer networks. Pola Schwöbel, Frederik Rahbæk Warburg, Martin Jørgensen, Kristoffer Hougaard Madsen, Søren Hauberg |
| 2022 | Probabilistic surrogate networks for simulators with unbounded randomness. Andreas Munk, Berend Zwartsenberg, Adam Scibior, Atilim Günes Baydin, Andrew Stewart, Goran Fernlund, Anoush Poursartip, Frank Wood |
| 2022 | Proportional allocation of indivisible resources under ordinal and uncertain preferences. Zihao Li, Xiaohui Bei, Zhenzhen Yan |
| 2022 | Quadratic metric elicitation for fairness and beyond. Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Oluwasanmi Koyejo |
| 2022 | Quantification of Credal Uncertainty in Machine Learning: A Critical Analysis and Empirical Comparison. Eyke Hüllermeier, Sébastien Destercke, Mohammad Hossein Shaker |
| 2022 | Quantum perceptron revisited: Computational-statistical tradeoffs. Mathieu Roget, Giuseppe Di Molfetta, Hachem Kadri |
| 2022 | ReVar: Strengthening policy evaluation via reduced variance sampling. Subhojyoti Mukherjee, Josiah P. Hanna, Robert D. Nowak |
| 2022 | Recursive Monte Carlo and variational inference with auxiliary variables. Alexander K. Lew, Marco F. Cusumano-Towner, Vikash K. Mansinghka |
| 2022 | Reframed GES with a neural conditional dependence measure. Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen |
| 2022 | Regret guarantees for model-based reinforcement learning with long-term average constraints. Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal |
| 2022 | Reinforcement learning in many-agent settings under partial observability. Keyang He, Prashant Doshi, Bikramjit Banerjee |
| 2022 | ResIST: Layer-wise decomposition of ResNets for distributed training. Chen Dun, Cameron R. Wolfe, Christopher M. Jermaine, Anastasios Kyrillidis |
| 2022 | Research on video adversarial attack with long living cycle. Zeyu Zhao, Ke Xu, Xinghao Jiang, Tanfeng Sun |
| 2022 | Residual bootstrap exploration for stochastic linear bandit. Shuang Wu, Chi-hua Wang, Yuantong Li, Guang Cheng |
| 2022 | Resolving label uncertainty with implicit posterior models. Esther Rolf, Nikolay Malkin, Alexandros Graikos, Ana Jojic, Caleb Robinson, Nebojsa Jojic |
| 2022 | Restless and uncertain: Robust policies for restless bandits via deep multi-agent reinforcement learning. Jackson A. Killian, Lily Xu, Arpita Biswas, Milind Tambe |
| 2022 | Revisiting DP-Means: fast scalable algorithms via parallelism and delayed cluster creation. Or Dinari, Oren Freifeld |
| 2022 | Revisiting the general identifiability problem. Yaroslav Kivva, Ehsan Mokhtarian, Jalal Etesami, Negar Kiyavash |
| 2022 | Robust Bayesian recourse. Tuan-Duy H. Nguyen, Ngoc Bui, Duy Nguyen, Man-Chung Yue, Viet Anh Nguyen |
| 2022 | Robust expected information gain for optimal Bayesian experimental design using ambiguity sets. Jinwoo Go, Tobin Isaac |
| 2022 | Robust identifiability in linear structural equation models of causal inference. Karthik Abinav Sankararaman, Anand Louis, Navin Goyal |
| 2022 | Robust learning of tractable probabilistic models. Rohith Peddi, Tahrima Rahman, Vibhav Gogate |
| 2022 | Robust textual embedding against word-level adversarial attacks. Yichen Yang, Xiaosen Wang, Kun He |
| 2022 | Robustness of model predictions under extension. Tineke Blom, Joris M. Mooij |
| 2022 | SASH: Efficient secure aggregation based on SHPRG for federated learning. Zizhen Liu, Si Chen, Jing Ye, Junfeng Fan, Huawei Li, Xiaowei Li |
| 2022 | SENTINEL: taming uncertainty with ensemble based distributional reinforcement learning. Hannes Eriksson, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis |
| 2022 | SMT-based weighted model integration with structure awareness. Giuseppe Spallitta, Gabriele Masina, Paolo Morettin, Andrea Passerini, Roberto Sebastiani |
| 2022 | ST-MAML : A stochastic-task based method for task-heterogeneous meta-learning. Zhe Wang, Jake Grigsby, Arshdeep Sekhon, Yanjun Qi |
| 2022 | Safety aware changepoint detection for piecewise i.i.d. bandits. Subhojyoti Mukherjee |
| 2022 | Self-distribution distillation: efficient uncertainty estimation. Yassir Fathullah, Mark J. F. Gales |
| 2022 | Self-supervised representations for multi-view reinforcement learning. Huanhuan Yang, Dianxi Shi, Guojun Xie, Yingxuan Peng, Yi Zhang, Yantai Yang, Shaowu Yang |
| 2022 | Semi-supervised novelty detection using ensembles with regularized disagreement. Alexandru Tifrea, Eric Stavarache, Fanny Yang |
| 2022 | Semiparametric causal sufficient dimension reduction of multidimensional treatments. Razieh Nabi, Todd McNutt, Ilya Shpitser |
| 2022 | Sequential algorithmic modification with test data reuse. Jean Feng, Gene Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio, Alexej Gossmann |
| 2022 | Set-valued prediction in hierarchical classification with constrained representation complexity. Thomas Mortier, Eyke Hüllermeier, Krzysztof Dembczynski, Willem Waegeman |
| 2022 | Shifted compression framework: generalizations and improvements. Egor Shulgin, Peter Richtárik |
| 2022 | Shoring up the foundations: fusing model embeddings and weak supervision. Mayee F. Chen, Daniel Y. Fu, Dyah Adila, Michael Zhang, Frederic Sala, Kayvon Fatahalian, Christopher Ré |
| 2022 | Simplified and unified analysis of various learning problems by reduction to Multiple-Instance Learning. Daiki Suehiro, Eiji Takimoto |
| 2022 | Solving structured hierarchical games using differential backward induction. Zun Li, Feiran Jia, Aditya Mate, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Yevgeniy Vorobeychik |
| 2022 | Stability of SGD: Tightness analysis and improved bounds. Yikai Zhang, Wenjia Zhang, Sammy Bald, Vamsi Pingali, Chao Chen, Mayank Goswami |
| 2022 | Stackmix: a complementary mix algorithm. John Chen, Samarth Sinha, Anastasios Kyrillidis |
| 2022 | Sublinear time algorithms for greedy selection in high dimensions. Qi Chen, Kai Liu, Ruilong Yao, Hu Ding |
| 2022 | Superposing many tickets into one: A performance booster for sparse neural network training. Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy |
| 2022 | SymNet 2.0: Effectively handling Non-Fluents and Actions in Generalized Neural Policies for RDDL Relational MDPs. Vishal Sharma, Daman Arora, Florian Geißer, Mausam, Parag Singla |
| 2022 | Systematized event-aware learning for multi-object tracking. Hyemin Lee, Daijin Kim |
| 2022 | Temporal abstractions-augmented temporally contrastive learning: An alternative to the Laplacian in RL. Akram Erraqabi, Marlos C. Machado, Mingde Zhao, Sainbayar Sukhbaatar, Alessandro Lazaric, Ludovic Denoyer, Yoshua Bengio |
| 2022 | Test for non-negligible adverse shifts. Vathy M. Kamulete |
| 2022 | The optimal noise in noise-contrastive learning is not what you think. Omar Chehab, Alexandre Gramfort, Aapo Hyvärinen |
| 2022 | Toward learning human-aligned cross-domain robust models by countering misaligned features. Haohan Wang, Zeyi Huang, Hanlin Zhang, Yong Jae Lee, Eric P. Xing |
| 2022 | Towards painless policy optimization for constrained MDPs. Arushi Jain, Sharan Vaswani, Reza Babanezhad, Csaba Szepesváari, Doina Precup |
| 2022 | Towards unsupervised open world semantic segmentation. Svenja Uhlemeyer, Matthias Rottmann, Hanno Gottschalk |
| 2022 | Uncertainty in Artificial Intelligence, Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, UAI 2022, 1-5 August 2022, Eindhoven, The Netherlands. James Cussens, Kun Zhang |
| 2022 | Uncertainty-aware pseudo-labeling for quantum calculations. Kexin Huang, Vishnu Sresht, Brajesh K. Rai, Mykola Bordyuh |
| 2022 | Understanding and mitigating the limitations of prioritized experience replay. Yangchen Pan, Jincheng Mei, Amir-massoud Farahmand, Martha White, Hengshuai Yao, Mohsen Rohani, Jun Luo |
| 2022 | Using hierarchies to efficiently combine evidence with Dempster's rule of combination. Daira Pinto Prieto, Ronald de Haan |
| 2022 | VQ-Flows: Vector quantized local normalizing flows. Sahil Sidheekh, Chris B. Dock, Tushar Jain, Radu V. Balan, Maneesh Kumar Singh |
| 2022 | Variational message passing neural network for Maximum-A-Posteriori (MAP) inference. Zijun Cui, Hanjing Wang, Tian Gao, Kartik Talamadupula, Qiang Ji |
| 2022 | Variational multiple shooting for Bayesian ODEs with Gaussian processes. Pashupati Hegde, Çagatay Yildiz, Harri Lähdesmäki, Samuel Kaski, Markus Heinonen |
| 2022 | Variational- and metric-based deep latent space for out-of-distribution detection. Or Dinari, Oren Freifeld |
| 2022 | Voronoi density estimator for high-dimensional data: Computation, compactification and convergence. Vladislav Polianskii, Giovanni Luca Marchetti, Alexander Kravberg, Anastasiia Varava, Florian T. Pokorny, Danica Kragic |
| 2022 | X-MEN: guaranteed XOR-maximum entropy constrained inverse reinforcement learning. Fan Ding, Yexiang Xue |
| 2022 | ℓ Wanshan Li, Shamindra Shrotriya, Alessandro Rinaldo |