Table of Contents

• Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement LearningChristoph Dann, Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert. 1-12 [doi]
• Learning One Representation to Optimize All RewardsAhmed Touati, Yann Ollivier. 13-23 [doi]
• Matrix factorisation and the interpretation of geodesic distanceNick Whiteley, Annie Gray, Patrick Rubin-Delanchy. 24-38 [doi]
• UniDoc: Unified Pretraining Framework for Document UnderstandingJiuxiang Gu, Jason Kuen, Vlad I. Morariu, Handong Zhao, Rajiv Jain, Nikolaos Barmpalios, Ani Nenkova, Tong Sun. 39-50 [doi]
• Finding Discriminative Filters for Specific Degradations in Blind Super-ResolutionLiangbin Xie, Xintao Wang, Chao Dong, Zhongang Qi, Ying Shan. 51-61 [doi]
• Counterfactual Explanations Can Be ManipulatedDylan Slack, Anna Hilgard, Himabindu Lakkaraju, Sameer Singh 0001. 62-75 [doi]
• From Canonical Correlation Analysis to Self-supervised Graph Neural NetworksHengrui Zhang, Qitian Wu, Junchi Yan, David Wipf, Philip S. Yu. 76-89 [doi]
• BAST: Bayesian Additive Regression Spanning Trees for Complex Constrained DomainZhao Tang Luo, Huiyan Sang, Bani K. Mallick. 90-102 [doi]
• Hyperbolic Busemann Learning with Ideal PrototypesMina Ghadimi Atigh, Martin Keller-Ressel, Pascal Mettes. 103-115 [doi]
• Backward-Compatible Prediction Updates: A Probabilistic ApproachFrederik Träuble, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Peter V. Gehler. 116-128 [doi]
• Truncated Marginal Neural Ratio EstimationBenjamin Kurt Miller, Alex Cole, Patrick Forré, Gilles Louppe, Christoph Weniger. 129-143 [doi]
• ReAct: Out-of-distribution Detection With Rectified ActivationsYiyou Sun, Chuan Guo, Yixuan Li. 144-157 [doi]
• Non-local Latent Relation Distillation for Self-Adaptive 3D Human Pose EstimationJogendra Nath Kundu, Siddharth Seth, Anirudh Jamkhandi, Pradyumna YM, Varun Jampani, Anirban Chakraborty, Venkatesh Babu R.. 158-171 [doi]
• Fast Training of Neural Lumigraph Representations using Meta LearningAlexander W. Bergman, Petr Kellnhofer, Gordon Wetzstein. 172-186 [doi]
• Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex ProblemsStefano Sarao Mannelli, Pierfrancesco Urbani. 187-199 [doi]
• Multimodal Few-Shot Learning with Frozen Language ModelsMaria Tsimpoukelli, Jacob Menick, Serkan Cabi, S. M. Ali Eslami, Oriol Vinyals, Felix Hill. 200-212 [doi]
• Approximating the Permanent with Deep Rejection SamplingJuha Harviainen, Antti Röyskö, Mikko Koivisto. 213-224 [doi]
• Revisiting Model Stitching to Compare Neural RepresentationsYamini Bansal, Preetum Nakkiran, Boaz Barak. 225-236 [doi]
• AugMax: Adversarial Composition of Random Augmentations for Robust TrainingHaotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, Zhangyang Wang. 237-250 [doi]
• Habitat 2.0: Training Home Assistants to Rearrange their HabitatAndrew Szot, Alexander Clegg, Eric Undersander, Erik Wijmans, Yili Zhao, John Turner, Noah Maestre, Mustafa Mukadam, Devendra Singh Chaplot, Oleksandr Maksymets, Aaron Gokaslan, Vladimir Vondrus, Sameer Dharur, Franziska Meier, Wojciech Galuba, Angel X. Chang, Zsolt Kira, Vladlen Koltun, Jitendra Malik, Manolis Savva, Dhruv Batra. 251-266 [doi]
• Time Discretization-Invariant Safe Action Repetition for Policy Gradient MethodsSeohong Park, Jaekyeom Kim, Gunhee Kim. 267-279 [doi]
• Meta-Learning Reliable Priors in the Function SpaceJonas Rothfuss, Dominique Heyn, Jinfan Chen, Andreas Krause 0001. 280-293 [doi]
• VoiceMixer: Adversarial Voice Style MixupSang-Hoon Lee, Ji-Hoon Kim, Hyunseung Chung, Seong-Whan Lee. 294-308 [doi]
• Predicting What You Already Know Helps: Provable Self-Supervised LearningJason D. Lee, Qi Lei, Nikunj Saunshi, Jiacheng Zhuo. 309-323 [doi]
• Oracle Complexity in Nonsmooth Nonconvex OptimizationGuy Kornowski, Ohad Shamir. 324-334 [doi]
• CentripetalText: An Efficient Text Instance Representation for Scene Text DetectionTao Sheng, Jie Chen, Zhouhui Lian. 335-346 [doi]
• Learning to Select Exogenous Events for Marked Temporal Point ProcessPing Zhang, Rishabh K. Iyer, Ashish Tendulkar, Gaurav Aggarwal, Abir De. 347-361 [doi]
• DRIVE: One-bit Distributed Mean EstimationShay Vargaftik, Ran Ben-Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben-Itzhak, Michael Mitzenmacher. 362-377 [doi]
• Learning Space Partitions for Path PlanningKevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian. 378-391 [doi]
• Progressive Feature Interaction Search for Deep Sparse NetworkChen Gao, Yinfeng Li, Quanming Yao, Depeng Jin, Yong Li 0008. 392-403 [doi]
• Local Explanation of Dialogue Response GenerationYi-Lin Tuan, Connor Pryor, Wenhu Chen, Lise Getoor, William Yang Wang. 404-416 [doi]
• Scalable Inference in SDEs by Direct Matching of the Fokker-Planck-Kolmogorov EquationArno Solin, Ella Tamir, Prakhar Verma. 417-429 [doi]
• The Complexity of Bayesian Network Learning: Revisiting the SuperstructureRobert Ganian, Viktoriia Korchemna. 430-442 [doi]
• Fast Tucker Rank Reduction for Non-Negative Tensors Using Mean-Field ApproximationKazu Ghalamkari, Mahito Sugiyama. 443-454 [doi]
• Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization BoundValentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj. 455-467 [doi]
• Numerical influence of ReLU'(0) on backpropagationDavid Bertoin, Jérôme Bolte, Sébastien Gerchinovitz, Edouard Pauwels. 468-479 [doi]
• A Contrastive Learning Approach for Training Variational Autoencoder PriorsJyoti Aneja, Alexander G. Schwing, Jan Kautz, Arash Vahdat. 480-493 [doi]
• What training reveals about neural network complexityAndreas Loukas, Marinos Poiitis, Stefanie Jegelka. 494-508 [doi]
• Class-agnostic Reconstruction of Dynamic Objects from VideosZhongzheng Ren, Xiaoming Zhao, Alexander G. Schwing. 509-522 [doi]
• Unique sparse decomposition of low rank matricesDian Jin, Xin Bing, Yuqian Zhang. 523-535 [doi]
• Neighborhood Reconstructing AutoencodersYonghyeon Lee, Hyeokjun Kwon, Frank C. Park 0001. 536-546 [doi]
• TopicNet: Semantic Graph-Guided Topic DiscoveryZhibin Duan, Yishi Xu, Bo Chen 0001, Dongsheng Wang 0003, Chaojie Wang 0001, Mingyuan Zhou. 547-559 [doi]
• (Almost) Free Incentivized Exploration from Decentralized Learning AgentsChengshuai Shi, Haifeng Xu, Wei Xiong, Cong Shen. 560-571 [doi]
• Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space LayersAlbert Gu, Isys Johnson, Karan Goel, Khaled Saab, Tri Dao, Atri Rudra, Christopher Ré. 572-585 [doi]
• Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial RobustnessZifeng Wang 0002, Tong Jian, Aria Masoomi, Stratis Ioannidis, Jennifer G. Dy. 586-597 [doi]
• T-LoHo: A Bayesian Regularization Model for Structured Sparsity and Smoothness on GraphsChangwoo J. Lee, Zhao Tang Luo, Huiyan Sang. 598-609 [doi]
• The Utility of Explainable AI in Ad Hoc Human-Machine TeamingRohan R. Paleja, Muyleng Ghuy, Nadun Ranawaka Arachchige, Reed Jensen, Matthew Gombolay. 610-623 [doi]
• Subgoal Search For Complex Reasoning TasksKonrad Czechowski, Tomasz Odrzygózdz, Marek Zbysinski, Michal Zawalski, Krzysztof Olejnik, Yuhuai Wu, Lukasz Kucinski, Piotr Milos. 624-638 [doi]
• MCMC Variational Inference via Uncorrected Hamiltonian AnnealingTomas Geffner, Justin Domke. 639-651 [doi]
• Landmark-RxR: Solving Vision-and-Language Navigation with Fine-Grained Alignment SupervisionKeji He, Yan Huang 0008, Qi Wu 0001, Jianhua Yang, Dong An, Shuanglin Sima, Liang Wang 0001. 652-663 [doi]
• A Winning Hand: Compressing Deep Networks Can Improve Out-of-Distribution RobustnessJames Diffenderfer, Brian R. Bartoldson, Shreya Chaganti, Jize Zhang, Bhavya Kailkhura. 664-676 [doi]
• On the Importance of Gradients for Detecting Distributional Shifts in the WildRui Huang, Andrew Geng, Yixuan Li. 677-689 [doi]
• Iterative Methods for Private Synthetic Data: Unifying Framework and New MethodsTerrance Liu, Giuseppe Vietri, Steven Wu 0001. 690-702 [doi]
• Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit ParameterizationClement Gehring, Kenji Kawaguchi, Jiaoyang Huang, Leslie Pack Kaelbling. 703-714 [doi]
• Mirror Langevin Monte Carlo: the Case Under IsoperimetryQijia Jiang. 715-725 [doi]
• Do Different Tracking Tasks Require Different Appearance Models?Zhongdao Wang, Hengshuang Zhao, Ya-Li Li 0001, Shengjin Wang, Philip H. S. Torr, Luca Bertinetto. 726-738 [doi]
• Towards robust vision by multi-task learning on monkey visual cortexShahd Safarani, Arne Nix, Konstantin Willeke, Santiago A. Cadena, Kelli Restivo, George H. Denfield, Andreas S. Tolias, Fabian H. Sinz. 739-751 [doi]
• Arbitrary Conditional Distributions with EnergyRyan R. Strauss, Junier B. Oliva. 752-763 [doi]
• Learning Domain Invariant Representations in Goal-conditioned Block MDPsBeining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael R. Zhang, Jimmy Ba. 764-776 [doi]
• Near-Optimal Multi-Perturbation Experimental Design for Causal Structure LearningScott Sussex, Caroline Uhler, Andreas Krause 0001. 777-788 [doi]
• Fuzzy Clustering with Similarity QueriesWasim Huleihel, Arya Mazumdar, Soumyabrata Pal. 789-801 [doi]
• Improving black-box optimization in VAE latent space using decoder uncertaintyPascal Notin, José Miguel Hernández-Lobato, Yarin Gal. 802-814 [doi]
• Sample Selection for Fair and Robust TrainingYuji Roh, Kangwook Lee 0001, Steven Whang, Changho Suh. 815-827 [doi]
• NeurWIN: Neural Whittle Index Network For Restless Bandits Via Deep RLKhaled Nakhleh, Santosh Ganji, Ping-Chun Hsieh, I-Hong Hou, Srinivas Shakkottai. 828-839 [doi]
• Sageflow: Robust Federated Learning against Both Stragglers and AdversariesJungwuk Park, Dong-Jun Han, Minseok Choi, Jaekyun Moon. 840-851 [doi]
• Alias-Free Generative Adversarial NetworksTero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, Timo Aila. 852-863 [doi]
• Noise2Score: Tweedie's Approach to Self-Supervised Image Denoising without Clean ImagesKwanyoung Kim, Jong Chul Ye. 864-874 [doi]
• Continuous Mean-Covariance BanditsYihan Du, Siwei Wang, Zhixuan Fang, Longbo Huang. 875-886 [doi]
• Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and LanguageMingyu Ding, Zhenfang Chen, Tao Du 0001, Ping Luo 0002, Josh Tenenbaum 0001, Chuang Gan. 887-899 [doi]
• Solving Soft Clustering Ensemble via $k$-Sparse Discrete Wasserstein BarycenterRuizhe Qin, Mengying Li, Hu Ding. 900-913 [doi]
• Bayesian Adaptation for Covariate ShiftAurick Zhou, Sergey Levine. 914-927 [doi]
• Perturb-and-max-product: Sampling and learning in discrete energy-based modelsMiguel Lázaro-Gredilla, Antoine Dedieu, Dileep George. 928-940 [doi]
• Towards Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum GamesXiangyu Liu, Hangtian Jia, Ying Wen, Yujing Hu, Yingfeng Chen, Changjie Fan, Zhipeng Hu, Yaodong Yang 0001. 941-952 [doi]
• Towards Better Understanding of Training Certifiably Robust Models against Adversarial ExamplesSungyoon Lee, Woojin Lee, Jinseong Park, Jaewook Lee 0001. 953-964 [doi]
• Mitigating Covariate Shift in Imitation Learning via Offline Data With Partial CoverageJonathan D. Chang, Masatoshi Uehara, Dhruv Sreenivas, Rahul Kidambi, Wen Sun. 965-979 [doi]
• Global Filter Networks for Image ClassificationYongming Rao, Wenliang Zhao, Zheng Zhu, Jiwen Lu, Jie Zhou 0001. 980-993 [doi]
• Catastrophic Data Leakage in Vertical Federated LearningXiao Jin, Pin-Yu Chen, Chia-Yi Hsu, Chia-Mu Yu, Tianyi Chen. 994-1006 [doi]
• Fault-Tolerant Federated Reinforcement Learning with Theoretical GuaranteeFlint Xiaofeng Fan, Yining Ma 0001, Zhongxiang Dai, Wei Jing, Cheston Tan, Bryan Kian Hsiang Low. 1007-1021 [doi]
• Compacter: Efficient Low-Rank Hypercomplex Adapter LayersRabeeh Karimi Mahabadi, James Henderson 0001, Sebastian Ruder. 1022-1035 [doi]
• Distilling Image Classifiers in Object DetectorsShuxuan Guo, Jose M. Alvarez, Mathieu Salzmann. 1036-1047 [doi]
• Subgroup Generalization and Fairness of Graph Neural NetworksJiaqi Ma 0001, Junwei Deng, Qiaozhu Mei. 1048-1061 [doi]
• Scaling Neural Tangent Kernels via Sketching and Random FeaturesAmir Zandieh, Insu Han, Haim Avron, Neta Shoham, Chaewon Kim, Jinwoo Shin. 1062-1073 [doi]
• BatchQuant: Quantized-for-all Architecture Search with Robust QuantizerHaoping Bai, Meng Cao, Ping Huang, Jiulong Shan. 1074-1085 [doi]
• Long Short-Term Transformer for Online Action DetectionMingze Xu, Yuanjun Xiong, Hao Chen, Xinyu Li, Wei Xia, Zhuowen Tu, Stefano Soatto. 1086-1099 [doi]
• Near Optimal Policy Optimization via REPSAldo Pacchiano, Jonathan N. Lee, Peter L. Bartlett, Ofir Nachum. 1100-1110 [doi]
• Self-Consistent Models and ValuesGregory Farquhar, Kate Baumli, Zita Marinho, Angelos Filos, Matteo Hessel, Hado Philip van Hasselt, David Silver. 1111-1125 [doi]
• Learning on Random Balls is Sufficient for Estimating (Some) Graph ParametersTakanori Maehara, Hoang NT. 1126-1141 [doi]
• Risk-Averse Bayes-Adaptive Reinforcement LearningMarc Rigter, Bruno Lacerda, Nick Hawes. 1142-1154 [doi]
• Iterative Connecting Probability Estimation for NetworksYichen Qin, Linhan Yu, Yang Li. 1155-1166 [doi]
• Learning to Adapt via Latent Domains for Adaptive Semantic SegmentationYunan Liu, Shanshan Zhang, Yang Li, Jian Yang 0003. 1167-1178 [doi]
• Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution DetectionKoby Bibas, Meir Feder, Tal Hassner. 1179-1191 [doi]
• Prototypical Cross-Attention Networks for Multiple Object Tracking and SegmentationLei Ke, Xia Li, Martin Danelljan, Yu-Wing Tai, Chi-Keung Tang, Fisher Yu. 1192-1203 [doi]
• Algorithmic Instabilities of Accelerated Gradient DescentAmit Attia, Tomer Koren. 1204-1214 [doi]
• Learning Optimal Predictive ChecklistsHaoran Zhang, Quaid Morris, Berk Ustun, Marzyeh Ghassemi. 1215-1229 [doi]
• Finite Sample Analysis of Average-Reward TD Learning and $Q$-LearningSheng Zhang, Zhe Zhang, Siva Theja Maguluri. 1230-1242 [doi]
• Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs HyperbolicAtsushi Suzuki, Atsushi Nitanda, Jing Wang 0023, Linchuan Xu, Kenji Yamanishi, Marc Cavazza. 1243-1255 [doi]
• Gradient Starvation: A Learning Proclivity in Neural NetworksMohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie. 1256-1272 [doi]
• Offline Reinforcement Learning as One Big Sequence Modeling ProblemMichael Janner, Qiyang Li, Sergey Levine. 1273-1286 [doi]
• Optimality and Stability in Federated Learning: A Game-theoretic ApproachKate Donahue, Jon M. Kleinberg. 1287-1298 [doi]
• Understanding Deflation Process in Over-parametrized Tensor DecompositionRong Ge 0001, Yunwei Ren, Xiang Wang 0011, Mo Zhou. 1299-1311 [doi]
• Privately Learning SubspacesVikrant Singhal, Thomas Steinke 0002. 1312-1324 [doi]
• On the Value of Interaction and Function Approximation in Imitation LearningNived Rajaraman, Yanjun Han, Lin Yang 0011, Jingbo Liu, Jiantao Jiao, Kannan Ramchandran. 1325-1336 [doi]
• Shapeshifter: a Parameter-efficient Transformer using Factorized Reshaped MatricesAliakbar Panahi, Seyran Saeedi, Tom Arodz. 1337-1350 [doi]
• The Adaptive Doubly Robust Estimator and a Paradox Concerning Logging PolicyMasahiro Kato, Kenichiro McAlinn, Shota Yasui. 1351-1364 [doi]
• Regularized Softmax Deep Multi-Agent Q-LearningLing Pan, Tabish Rashid, Bei Peng, Longbo Huang, Shimon Whiteson. 1365-1377 [doi]
• Physics-Aware Downsampling with Deep Learning for Scalable Flood ModelingNiv Giladi, Zvika Ben-Haim, Sella Nevo, Yossi Matias, Daniel Soudry. 1378-1389 [doi]
• Systematic Generalization with Edge TransformersLeon Bergen, Timothy J. O'Donnell, Dzmitry Bahdanau. 1390-1402 [doi]
• TransformerFusion: Monocular RGB Scene Reconstruction using TransformersAljaz Bozic, Pablo R. Palafox, Justus Thies, Angela Dai, Matthias Nießner. 1403-1414 [doi]
• Maximum Likelihood Training of Score-Based Diffusion ModelsYang Song 0011, Conor Durkan, Iain Murray 0001, Stefano Ermon. 1415-1428 [doi]
• Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix FactorizationTian Ye, Simon S. Du. 1429-1439 [doi]
• Adaptive Data Augmentation on Temporal GraphsYiwei Wang 0001, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Siddharth Bhatia 0001, Bryan Hooi. 1440-1452 [doi]
• Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and BeyondD. Khuê Lê-Huu, Karteek Alahari. 1453-1467 [doi]
• Terra: Imperative-Symbolic Co-Execution of Imperative Deep Learning ProgramsTaebum Kim, Eunji Jeong, Geon Woo Kim, Yunmo Koo, Sehoon Kim, Gyeong-In Yu, Byung-Gon Chun. 1468-1480 [doi]
• Uniform Sampling over Episode DifficultySébastien M. R. Arnold, Guneet S. Dhillon, Avinash Ravichandran, Stefano Soatto. 1481-1493 [doi]
• Scalable Intervention Target Estimation in Linear ModelsBurak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer. 1494-1505 [doi]
• Play to Grade: Testing Coding Games as Classifying Markov Decision ProcessAllen Nie, Emma Brunskill, Chris Piech. 1506-1518 [doi]
• Distributional Reinforcement Learning for Multi-Dimensional Reward FunctionsPushi Zhang, Xiaoyu Chen, Li Zhao 0007, Wei Xiong, Tao Qin, Tie-Yan Liu. 1519-1529 [doi]
• Differentiable Unsupervised Feature Selection based on a Gated LaplacianOfir Lindenbaum, Uri Shaham, Erez Peterfreund, Jonathan Svirsky, Nicolas Casey, Yuval Kluger. 1530-1542 [doi]
• Smooth Bilevel Programming for Sparse RegularizationClarice Poon, Gabriel Peyré. 1543-1555 [doi]
• Grounding Representation Similarity Through Statistical TestingFrances Ding, Jean-Stanislas Denain, Jacob Steinhardt. 1556-1568 [doi]
• A Consciousness-Inspired Planning Agent for Model-Based Reinforcement LearningMingde Zhao, Zhen Liu 0019, Sitao Luan, Shuyuan Zhang, Doina Precup, Yoshua Bengio. 1569-1581 [doi]
• Reward-Free Model-Based Reinforcement Learning with Linear Function ApproximationWeitong Zhang, Dongruo Zhou, Quanquan Gu. 1582-1593 [doi]
• Beltrami Flow and Neural Diffusion on GraphsBen Chamberlain 0001, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong 0001, Michael M. Bronstein. 1594-1609 [doi]
• Think Big, Teach Small: Do Language Models Distil Occam's Razor?Gonzalo Jaimovitch-Lopez, David Castellano Falcón, César Ferri, José Hernández-Orallo. 1610-1623 [doi]
• Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICAHermanni Hälvä, Sylvain Le Corff, Luc Lehéricy, Jonathan So, Yongjie Zhu, Elisabeth Gassiat, Aapo Hyvärinen. 1624-1633 [doi]
• Conditionally Parameterized, Discretization-Aware Neural Networks for Mesh-Based Modeling of Physical SystemsJiayang Xu, Aniruddhe Pradhan, Karthik Duraisamy. 1634-1645 [doi]
• USCO-Solver: Solving Undetermined Stochastic Combinatorial Optimization ProblemsGuangmo Tong. 1646-1659 [doi]
• Adaptive Conformal Inference Under Distribution ShiftIsaac Gibbs, Emmanuel J. Candès. 1660-1672 [doi]
• Periodic Activation Functions Induce StationarityLassi Meronen, Martin Trapp 0001, Arno Solin. 1673-1685 [doi]
• Towards Optimal Strategies for Training Self-Driving Perception Models in SimulationDavid Acuna, Jonah Philion, Sanja Fidler. 1686-1699 [doi]
• KS-GNN: Keywords Search over Incomplete Graphs via Graphs Neural NetworkYu Hao 0003, Xin Cao 0001, Yufan Sheng, Yixiang Fang, Wei Wang 0011. 1700-1712 [doi]
• Reconstruction for Powerful Graph RepresentationsLeonardo Cotta, Christopher Morris 0001, Bruno Ribeiro 0001. 1713-1726 [doi]
• Revealing and Protecting Labels in Distributed TrainingTrung Dang, Om Thakkar 0001, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Françoise Beaufays. 1727-1738 [doi]
• Solving Graph-based Public Goods Games with Tree Search and Imitation LearningVictor-Alexandru Darvariu, Stephen Hailes, Mirco Musolesi. 1739-1751 [doi]
• Stochastic Optimization of Areas Under Precision-Recall Curves with Provable ConvergenceQi Qi, Youzhi Luo, Zhao Xu, Shuiwang Ji, Tianbao Yang. 1752-1765 [doi]
• Transfer Learning of Graph Neural Networks with Ego-graph Information MaximizationQi Zhu 0008, Carl Yang, Yidan Xu, Haonan Wang, Chao Zhang 0014, Jiawei Han 0001. 1766-1779 [doi]
• You are caught stealing my winning lottery ticket! Making a lottery ticket claim its ownershipXuxi Chen, Tianlong Chen, Zhenyu Zhang, Zhangyang Wang. 1780-1791 [doi]
• Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max OptimizationHaochuan Li, Yi Tian, Jingzhao Zhang, Ali Jadbabaie. 1792-1804 [doi]
• Early-stopped neural networks are consistentZiwei Ji, Justin D. Li, Matus Telgarsky. 1805-1817 [doi]
• NxMTransformer: Semi-Structured Sparsification for Natural Language Understanding via ADMMConnor Holmes, Minjia Zhang, Yuxiong He, Bo Wu 0002. 1818-1830 [doi]
• Reliable Decisions with Threshold CalibrationRoshni Sahoo, Shengjia Zhao, Alyssa Chen, Stefano Ermon. 1831-1844 [doi]
• End-to-End Weak SupervisionSalva Rühling Cachay, Benedikt Boecking, Artur Dubrawski. 1845-1857 [doi]
• Shift Invariance Can Reduce Adversarial RobustnessVasu Singla, Songwei Ge, Ronen Basri, David W. Jacobs. 1858-1871 [doi]
• Wisdom of the Crowd Voting: Truthful Aggregation of Voter Information and PreferencesGrant Schoenebeck, Biaoshuai Tao. 1872-1883 [doi]
• Replay-Guided Adversarial Environment DesignMinqi Jiang, Michael Dennis 0001, Jack Parker-Holder, Jakob N. Foerster, Edward Grefenstette, Tim Rocktäschel. 1884-1897 [doi]
• There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement LearningNathan Grinsztajn, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist. 1898-1911 [doi]
• Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in RoboticsIngmar Schubert, Danny Driess, Ozgur S. Oguz, Marc Toussaint. 1912-1924 [doi]
• Self-Diagnosing GAN: Diagnosing Underrepresented Samples in Generative Adversarial NetworksJinhee Lee, Haeri Kim, Youngkyu Hong, Hye Won Chung. 1925-1938 [doi]
• Online Multi-Armed Bandits with Adaptive InferenceMaria Dimakopoulou, Zhimei Ren, Zhengyuan Zhou. 1939-1951 [doi]
• Efficient Truncated Linear Regression with Unknown Noise VarianceConstantinos Daskalakis, Patroklos Stefanou, Rui Yao, Emmanouil Zampetakis. 1952-1963 [doi]
• Breaking the Dilemma of Medical Image-to-image TranslationLingke Kong, Chenyu Lian, Detian Huang, Zhenjiang Li, Yanle Hu, Qichao Zhou. 1964-1978 [doi]
• Temporally Abstract Partial ModelsKhimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, Doina Precup. 1979-1991 [doi]
• TransMatcher: Deep Image Matching Through Transformers for Generalizable Person Re-identificationShengCai Liao, Ling Shao 0001. 1992-2003 [doi]
• Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPsHarsh Satija, Philip S. Thomas, Joelle Pineau, Romain Laroche. 2004-2017 [doi]
• Is Automated Topic Model Evaluation Broken? The Incoherence of CoherenceAlexander Miserlis Hoyle, Pranav Goel, Andrew Hian-Cheong, Denis Peskov, Jordan L. Boyd-Graber, Philip Resnik. 2018-2033 [doi]
• INDIGO: GNN-Based Inductive Knowledge Graph Completion Using Pair-Wise EncodingShuwen Liu, Bernardo Cuenca Grau, Ian Horrocks, Egor V. Kostylev. 2034-2045 [doi]
• Do Input Gradients Highlight Discriminative Features?Harshay Shah, Prateek Jain 0002, Praneeth Netrapalli. 2046-2059 [doi]
• Improving Conditional Coverage via Orthogonal Quantile RegressionShai Feldman, Stephen Bates, Yaniv Romano. 2060-2071 [doi]
• Minimizing Polarization and Disagreement in Social Networks via Link RecommendationLiwang Zhu, Qi Bao, Zhongzhi Zhang. 2072-2084 [doi]
• Adversarial Attacks on Black Box Video Classifiers: Leveraging the Power of Geometric TransformationsShasha Li, Abhishek Aich, Shitong Zhu, M. Salman Asif, Chengyu Song, Amit K. Roy Chowdhury, Srikanth V. Krishnamurthy. 2085-2096 [doi]
• Optimal Rates for Random Order Online OptimizationUri Sherman, Tomer Koren, Yishay Mansour. 2097-2108 [doi]
• Discrete-Valued Neural CommunicationDianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael C. Mozer, Yoshua Bengio. 2109-2121 [doi]
• Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr\"om MethodYifan Chen, Qi Zeng, Heng Ji, Yun Yang. 2122-2135 [doi]
• TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image ClassificationZhuchen Shao, Hao Bian, Yang Chen, Yifeng Wang, Jian Zhang, Xiangyang Ji, Yongbing Zhang. 2136-2147 [doi]
• Multi-view Contrastive Graph ClusteringErlin Pan, Zhao Kang 0001. 2148-2159 [doi]
• Inverse-Weighted Survival GamesXintian Han, Mark Goldstein, Aahlad Manas Puli, Thomas Wies, Adler J. Perotte, Rajesh Ranganath. 2160-2172 [doi]
• Generalization Bounds for Meta-Learning via PAC-Bayes and Uniform StabilityAlec Farid, Anirudha Majumdar. 2173-2186 [doi]
• Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume ImprovementSamuel Daulton, Maximilian Balandat, Eytan Bakshy. 2187-2200 [doi]
• Evolution Gym: A Large-Scale Benchmark for Evolving Soft RobotsJagdeep Singh Bhatia, Holly Jackson, Yunsheng Tian, Jie Xu 0028, Wojciech Matusik. 2201-2214 [doi]
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• Circa: Stochastic ReLUs for Private Deep LearningZahra Ghodsi, Nandan Kumar Jha, Brandon Reagen, Siddharth Garg. 2241-2252 [doi]
• Reinforcement Learning in Reward-Mixing MDPsJeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor. 2253-2264 [doi]
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• Explaining Hyperparameter Optimization via Partial Dependence PlotsJulia Moosbauer, Julia Herbinger, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl. 2280-2291 [doi]
• Robustifying Algorithms of Learning Latent Trees with Vector VariablesFengzhuo Zhang, Vincent Y. F. Tan. 2292-2302 [doi]
• Representation Learning on Spatial NetworksZheng Zhan 0001, Liang Zhao. 2303-2318 [doi]
• Continuous-time edge modelling using non-parametric point processesXuhui Fan, Bin Li 0015, Feng Zhou 0011, Scott A. Sisson. 2319-2330 [doi]
• Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through timeFeng Zhu, Andrew R. Sedler, Harrison A. Grier, Nauman Ahad, Mark A. Davenport, Matthew T. Kaufman, Andrea Giovannucci, Chethan Pandarinath. 2331-2345 [doi]
• Memory-efficient Patch-based Inference for Tiny Deep LearningJi Lin 0002, Wei-Ming Chen, Han Cai, Chuang Gan, Song Han 0003. 2346-2358 [doi]
• Self-Interpretable Model with Transformation Equivariant InterpretationYipei Wang, Xiaoqian Wang 0001. 2359-2372 [doi]
• Solving Min-Max Optimization with Hidden Structure via Gradient Descent AscentEmmanouil-Vasileios Vlatakis-Gkaragkounis, Lampros Flokas, Georgios Piliouras. 2373-2386 [doi]
• Preserved central model for faster bidirectional compression in distributed settingsConstantin Philippenko, Aymeric Dieuleveut. 2387-2399 [doi]
• Understanding Instance-based Interpretability of Variational Auto-EncodersZhifeng Kong, Kamalika Chaudhuri. 2400-2412 [doi]
• Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single ImageFeng Liu 0037, Xiaoming Liu 0002. 2413-2426 [doi]
• Test-Time Classifier Adjustment Module for Model-Agnostic Domain GeneralizationYusuke Iwasawa, Yutaka Matsuo. 2427-2440 [doi]
• Luna: Linear Unified Nested AttentionXuezhe Ma, Xiang Kong, Sinong Wang, Chunting Zhou, Jonathan May, Hao Ma, Luke Zettlemoyer. 2441-2453 [doi]
• Iterative Causal Discovery in the Possible Presence of Latent Confounders and Selection BiasRaanan Y. Rohekar, Shami Nisimov, Yaniv Gurwicz, Gal Novik. 2454-2465 [doi]
• Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RLCharles Packer, Pieter Abbeel, Joseph E. Gonzalez. 2466-2477 [doi]
• A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive PhysicsKai Xu, Akash Srivastava, Dan Gutfreund, Felix Sosa, Tomer D. Ullman, Josh Tenenbaum 0001, Charles Sutton. 2478-2490 [doi]
• Associating Objects with Transformers for Video Object SegmentationZongxin Yang, Yunchao Wei, Yi Yang 0001. 2491-2502 [doi]
• Automatic Symmetry Discovery with Lie Algebra Convolutional NetworkNima Dehmamy, Robin Walters, Yanchen Liu, Dashun Wang, Rose Yu. 2503-2515 [doi]
• Zero Time Waste: Recycling Predictions in Early Exit Neural NetworksMaciej Wolczyk, Bartosz Wójcik, Klaudia Balazy, Igor T. Podolak, Jacek Tabor, Marek Smieja, Tomasz Trzcinski. 2516-2528 [doi]
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• ReSSL: Relational Self-Supervised Learning with Weak AugmentationMingkai Zheng, Shan You, Fei Wang 0032, Chen Qian 0006, Changshui Zhang, Xiaogang Wang 0001, Chang Xu 0002. 2543-2555 [doi]
• Learning to See by Looking at NoiseManel Baradad Jurjo, Jonas Wulff, Tongzhou Wang 0001, Phillip Isola, Antonio Torralba 0001. 2556-2569 [doi]
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• Learning Conjoint Attentions for Graph Neural NetsTiantian He, Yew-Soon Ong, Lu Bai 0005. 2641-2653 [doi]
• Hybrid Regret Bounds for Combinatorial Semi-Bandits and Adversarial Linear BanditsShinji Ito. 2654-2667 [doi]
• Pay Better Attention to Attention: Head Selection in Multilingual and Multi-Domain Sequence ModelingHongyu Gong, Yun Tang, Juan Pino, Xian Li. 2668-2681 [doi]
• Cardinality-Regularized Hawkes-Granger ModelTsuyoshi Idé, Georgios Kollias, Dzung T. Phan, Naoki Abe. 2682-2694 [doi]
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• Constrained Robust Submodular PartitioningShengjie Wang, Tianyi Zhou, Chandrashekhar Lavania, Jeff A. Bilmes. 2721-2732 [doi]
• Online Knapsack with Frequency PredictionsSungjin Im, Ravi Kumar 0001, Mahshid Montazer Qaem, Manish Purohit. 2733-2743 [doi]
• On Component Interactions in Two-Stage Recommender SystemsJiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus. 2744-2757 [doi]
• Lip to Speech Synthesis with Visual Context Attentional GANMinsu Kim, Joanna Hong, Yong Man Ro. 2758-2770 [doi]
• Non-convex Distributionally Robust Optimization: Non-asymptotic AnalysisJikai Jin, Bohang Zhang, Haiyang Wang, Liwei Wang 0001. 2771-2782 [doi]
• Goal-Aware Cross-Entropy for Multi-Target Reinforcement LearningKibeom Kim, Min Whoo Lee, Yoonsung Kim, Je-hwan Ryu, Min Su Lee, Byoung-Tak Zhang. 2783-2795 [doi]
• Smooth Normalizing FlowsJonas Köhler 0001, Andreas Krämer, Frank Noé. 2796-2809 [doi]
• MetaAvatar: Learning Animatable Clothed Human Models from Few Depth ImagesShaofei Wang, Marko Mihajlovic, Qianli Ma, Andreas Geiger 0001, Siyu Tang 0001. 2810-2822 [doi]
• Distributed Principal Component Analysis with Limited CommunicationFoivos Alimisis, Peter Davies, Bart Vandereycken, Dan Alistarh. 2823-2834 [doi]
• Newton-LESS: Sparsification without Trade-offs for the Sketched Newton UpdateMichal Derezinski, Jonathan Lacotte, Mert Pilanci, Michael W. Mahoney. 2835-2847 [doi]
• Confident Anchor-Induced Multi-Source Free Domain AdaptationJiahua Dong, Zhen Fang, Anjin Liu, Gan Sun, Tongliang Liu. 2848-2860 [doi]
• Word2Fun: Modelling Words as Functions for Diachronic Word RepresentationBenyou Wang, Emanuele Di Buccio, Massimo Melucci. 2861-2872 [doi]
• Iteratively Reweighted Least Squares for Basis Pursuit with Global Linear Convergence RateChristian Kümmerle, Claudio Mayrink Verdun, Dominik Stöger. 2873-2886 [doi]
• Low-Rank Constraints for Fast Inference in Structured ModelsJustin T. Chiu, Yuntian Deng, Alexander M. Rush. 2887-2898 [doi]
• Accumulative Poisoning Attacks on Real-time DataTianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su 0006, Jun Zhu 0001. 2899-2912 [doi]
• UCB-based Algorithms for Multinomial Logistic Regression BanditsSanae Amani, Christos Thrampoulidis. 2913-2924 [doi]
• Estimating the Long-Term Effects of Novel TreatmentsKeith Battocchi, Eleanor Dillon, Maggie Hei, Greg Lewis, Miruna Oprescu, Vasilis Syrgkanis. 2925-2935 [doi]
• Dual Progressive Prototype Network for Generalized Zero-Shot LearningChaoqun Wang, Shaobo Min, Xuejin Chen, Xiaoyan Sun 0001, Houqiang Li. 2936-2948 [doi]
• Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample ComplexityKaiqing Zhang, Xiangyuan Zhang, Bin Hu, Tamer Basar. 2949-2964 [doi]
• G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher DiscriminatorsYunhui Long, Boxin Wang, Zhuolin Yang, Bhavya Kailkhura, Aston Zhang, Carl A. Gunter, Bo Li 0026. 2965-2977 [doi]
• On the Existence of The Adversarial Bayes ClassifierPranjal Awasthi, Natalie Frank, Mehryar Mohri. 2978-2990 [doi]
• Convex-Concave Min-Max Stackelberg GamesDenizalp Goktas, Amy Greenwald. 2991-3003 [doi]
• Misspecified Gaussian Process Bandit OptimizationIlija Bogunovic, Andreas Krause 0001. 3004-3015 [doi]
• Visual Adversarial Imitation Learning using Variational ModelsRafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn. 3016-3028 [doi]
• Object-Aware Regularization for Addressing Causal Confusion in Imitation LearningJongjin Park, Younggyo Seo, Chang Liu 0030, Li Zhao 0007, Tao Qin, Jinwoo Shin, Tie-Yan Liu. 3029-3042 [doi]
• Reliable and Trustworthy Machine Learning for Health Using Dataset Shift DetectionChunjong Park, Anas Awadalla, Tadayoshi Kohno, Shwetak N. Patel. 3043-3056 [doi]
• Multiclass Boosting and the Cost of Weak LearningNataly Brukhim, Elad Hazan, Shay Moran, Indraneel Mukherjee, Robert E. Schapire. 3057-3067 [doi]
• Partition-Based Formulations for Mixed-Integer Optimization of Trained ReLU Neural NetworksCalvin Tsay, Jan Kronqvist, Alexander Thebelt, Ruth Misener. 3068-3080 [doi]
• Hyperparameter Optimization Is Deceiving Us, and How to Stop ItA. Feder Cooper, Yucheng Lu, Jessica Forde, Christopher De Sa. 3081-3095 [doi]
• On the Convergence Theory of Debiased Model-Agnostic Meta-Reinforcement LearningAlireza Fallah 0001, Kristian Georgiev, Aryan Mokhtari, Asuman E. Ozdaglar. 3096-3107 [doi]
• 3D Pose Transfer with Correspondence Learning and Mesh RefinementChaoyue Song, Jiacheng Wei, Ruibo Li, Fayao Liu, Guosheng Lin. 3108-3120 [doi]
• Framing RNN as a kernel method: A neural ODE approachAdeline Fermanian, Pierre Marion, Jean-Philippe Vert, Gérard Biau. 3121-3134 [doi]
• Contextual Similarity Aggregation with Self-attention for Visual Re-rankingJianbo Ouyang, Hui Wu, Min Wang 0019, Wengang Zhou, Houqiang Li. 3135-3148 [doi]
• Can Information Flows Suggest Targets for Interventions in Neural Circuits?Praveen Venkatesh, Sanghamitra Dutta, Neil Mehta, Pulkit Grover. 3149-3162 [doi]
• AutoBalance: Optimized Loss Functions for Imbalanced DataMingchen Li, Xuechen Zhang, Christos Thrampoulidis, Jiasi Chen, Samet Oymak. 3163-3177 [doi]
• SyncTwin: Treatment Effect Estimation with Longitudinal OutcomesZhaozhi Qian, Yao Zhang, Ioana Bica, Angela M. Wood, Mihaela van der Schaar. 3178-3190 [doi]
• Statistical Query Lower Bounds for List-Decodable Linear RegressionIlias Diakonikolas, Daniel Kane, Ankit Pensia, Thanasis Pittas, Alistair Stewart. 3191-3204 [doi]
• Unsupervised Motion Representation Learning with Capsule AutoencodersZiwei Xu 0001, Xudong Shen, Yongkang Wong, Mohan S. Kankanhalli. 3205-3217 [doi]
• VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social MediaYizhou Zhang, Karishma Sharma, Yan Liu. 3218-3231 [doi]
• An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling OrdersXinmeng Huang, Kun Yuan, Xianghui Mao, Wotao Yin. 3232-3243 [doi]
• Exploring Forensic Dental Identification with Deep LearningYuan Liang, Weikun Han, Liang Qiu, Chen Wu, Yiting Shao, Kun Wang 0005, Lei He 0001. 3244-3258 [doi]
• Learning to Generate Realistic Noisy Images via Pixel-level Noise-aware Adversarial TrainingYuanhao Cai, Xiaowan Hu, Haoqian Wang, Yulun Zhang, Hanspeter Pfister, Donglai Wei. 3259-3270 [doi]
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• Dangers of Bayesian Model Averaging under Covariate ShiftPavel Izmailov, Patrick Nicholson, Sanae Lotfi, Andrew Gordon Wilson. 3309-3322 [doi]
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• Instance-dependent Label-noise Learning under a Structural Causal ModelYu Yao, Tongliang Liu, Mingming Gong, Bo Han 0003, Gang Niu 0001, Kun Zhang 0001. 4409-4420 [doi]
• Combining Human Predictions with Model Probabilities via Confusion Matrices and CalibrationGavin Kerrigan, Padhraic Smyth, Mark Steyvers. 4421-4434 [doi]
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• Influence Patterns for Explaining Information Flow in BERTKaiji Lu, Zifan Wang, Piotr Mardziel, Anupam Datta. 4461-4474 [doi]
• Robust Regression Revisited: Acceleration and Improved Estimation RatesArun Jambulapati, Jerry Li 0001, Tselil Schramm, Kevin Tian. 4475-4488 [doi]
• Automatic Unsupervised Outlier Model SelectionYue Zhao 0016, Ryan A. Rossi, Leman Akoglu. 4489-4502 [doi]
• Pruning Randomly Initialized Neural Networks with Iterative RandomizationDaiki Chijiwa, Shin'ya Yamaguchi, Yasutoshi Ida, Kenji Umakoshi, Tomohiro Inoue. 4503-4513 [doi]
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• Stability and Generalization of Bilevel Programming in Hyperparameter OptimizationFan Bao, Guoqiang Wu, Chongxuan Li, Jun Zhu 0001, Bo Zhang 0010. 4529-4541 [doi]
• Regime Switching BanditsXiang Zhou, Yi Xiong, Ningyuan Chen, Xuefeng Gao. 4542-4554 [doi]
• MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel MapsMuhammad Awais, Fengwei Zhou, Chuanlong Xie, Jiawei Li, Sung-Ho Bae, Zhenguo Li. 4555-4569 [doi]
• Localization, Convexity, and Star AggregationSuhas Vijaykumar. 4570-4581 [doi]
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• RoMA: Robust Model Adaptation for Offline Model-based OptimizationSihyun Yu, Sungsoo Ahn, Le Song, Jinwoo Shin. 4619-4631 [doi]
• Flexible Option LearningMartin Klissarov, Doina Precup. 4632-4646 [doi]
• Faster Directional Convergence of Linear Neural Networks under Spherically Symmetric DataDachao Lin, Ruoyu Sun 0001, Zhihua Zhang. 4647-4660 [doi]
• Online Facility Location with Multiple AdviceMatteo Almanza, Flavio Chierichetti, Silvio Lattanzi, Alessandro Panconesi, Giuseppe Re. 4661-4673 [doi]
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• Robust Online Correlation ClusteringSilvio Lattanzi, Benjamin Moseley, Sergei Vassilvitskii, Yuyan Wang, Rudy Zhou. 4688-4698 [doi]
• Neural Additive Models: Interpretable Machine Learning with Neural NetsRishabh Agarwal, Levi Melnick, Nicholas Frosst, Xuezhou Zhang, Benjamin Lengerich, Rich Caruana, Geoffrey E. Hinton. 4699-4711 [doi]
• Representation Learning for Event-based Visuomotor PoliciesSai Vemprala, Sami Mian, Ashish Kapoor. 4712-4724 [doi]
• Kernel Functional OptimisationArun Kumar Anjanapura Venkatesh, Alistair Shilton, Santu Rana, Sunil Gupta 0001, Svetha Venkatesh. 4725-4737 [doi]
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• Towards Robust Bisimulation Metric LearningMete Kemertas, Tristan Aumentado-Armstrong. 4764-4777 [doi]
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• Representation Learning Beyond Linear Prediction FunctionsZiping Xu, Ambuj Tewari. 4792-4804 [doi]
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• MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence FrontiersKrishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Sean Welleck, Yejin Choi, Zaïd Harchaoui. 4816-4828 [doi]
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• Limiting fluctuation and trajectorial stability of multilayer neural networks with mean field trainingHuy Tuan Pham, Phan-Minh Nguyen. 4843-4855 [doi]
• Medical Dead-ends and Learning to Identify High-Risk States and TreatmentsMehdi Fatemi, Taylor W. Killian, Jayakumar Subramanian, Marzyeh Ghassemi. 4856-4870 [doi]
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• High-probability Bounds for Non-Convex Stochastic Optimization with Heavy TailsAshok Cutkosky, Harsh Mehta. 4883-4895 [doi]
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• Offline RL Without Off-Policy EvaluationDavid Brandfonbrener, Will Whitney, Rajesh Ranganath, Joan Bruna. 4933-4946 [doi]
• Continuous vs. Discrete Optimization of Deep Neural NetworksOmer Elkabetz, Nadav Cohen. 4947-4960 [doi]
• CrypTen: Secure Multi-Party Computation Meets Machine LearningBrian Knott, Shobha Venkataraman, Awni Y. Hannun, Shubho Sengupta, Mark Ibrahim, Laurens van der Maaten. 4961-4973 [doi]
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• See More for Scene: Pairwise Consistency Learning for Scene ClassificationGongwei Chen, Xinhang Song, Bohan Wang, Shuqiang Jiang. 4987-4999 [doi]
• Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive LossJeff Z. HaoChen, Colin Wei, Adrien Gaidon, Tengyu Ma 0001. 5000-5011 [doi]
• Greedy Approximation Algorithms for Active Sequential Hypothesis TestingKyra Gan, Su Jia, Andrew A. Li. 5012-5024 [doi]
• When False Positive is Intolerant: End-to-End Optimization with Low FPR for Multipartite RankingPeisong Wen, Qianqian Xu, Zhiyong Yang 0001, Yuan He, Qingming Huang. 5025-5037 [doi]
• Convex Polytope Trees and its Application to VAEMohammadreza Armandpour, Ali Sadeghian, Mingyuan Zhou. 5038-5051 [doi]
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• Stability and Deviation Optimal Risk Bounds with Convergence Rate $O(1/n)$Yegor Klochkov, Nikita Zhivotovskiy. 5065-5076 [doi]
• SketchGen: Generating Constrained CAD SketchesWamiq Reyaz Para, Shariq Farooq Bhat, Paul Guerrero, Tom Kelly, Niloy J. Mitra, Leonidas J. Guibas, Peter Wonka. 5077-5088 [doi]
• CLDA: Contrastive Learning for Semi-Supervised Domain AdaptationAnkit Singh. 5089-5101 [doi]
• Differentially Private n-gram ExtractionKunho Kim, Sivakanth Gopi, Janardhan Kulkarni, Sergey Yekhanin. 5102-5111 [doi]
• Capturing implicit hierarchical structure in 3D biomedical images with self-supervised hyperbolic representationsJoy Hsu, Jeffrey Gu, Gong Her Wu, Wah Chiu, Serena Yeung. 5112-5123 [doi]
• Noisy Recurrent Neural NetworksSoon Hoe Lim, N. Benjamin Erichson, Liam Hodgkinson, Michael W. Mahoney. 5124-5137 [doi]
• Matrix encoding networks for neural combinatorial optimizationYeong-Dae Kwon, Jinho Choo, Iljoo Yoon, Minah Park, Duwon Park, Youngjune Gwon. 5138-5149 [doi]
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• Grounding Spatio-Temporal Language with TransformersTristan Karch, Laetitia Teodorescu, Katja Hofmann, Clément Moulin-Frier, Pierre-Yves Oudeyer. 5236-5249 [doi]
• Learning where to learn: Gradient sparsity in meta and continual learningJohannes von Oswald, Dominic Zhao, Seijin Kobayashi, Simon Schug, Massimo Caccia, Nicolas Zucchet, João Sacramento. 5250-5263 [doi]
• Domain Invariant Representation Learning with Domain Density TransformationsA. Tuan Nguyen, Toan Tran, Yarin Gal, Atilim Gunes Baydin. 5264-5275 [doi]
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• Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy EvaluationYunhao Tang, Tadashi Kozuno, Mark Rowland, Rémi Munos, Michal Valko. 5303-5315 [doi]
• Even your Teacher Needs Guidance: Ground-Truth Targets Dampen Regularization Imposed by Self-DistillationKenneth Borup, Lars Nørvang Andersen. 5316-5327 [doi]
• Compressing Neural Networks: Towards Determining the Optimal Layer-wise DecompositionLucas Liebenwein, Alaa Maalouf, Dan Feldman, Daniela Rus. 5328-5344 [doi]
• Equilibrium and non-Equilibrium regimes in the learning of Restricted Boltzmann MachinesAurélien Decelle, Cyril Furtlehner, Beatriz Seoane. 5345-5359 [doi]
• Imitation with Neural Density ModelsKuno Kim, Akshat Jindal, Yang Song 0011, Jiaming Song, Yanan Sui, Stefano Ermon. 5360-5372 [doi]
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• On the Representation of Solutions to Elliptic PDEs in Barron SpacesZiang Chen, Jianfeng Lu 0001, Yulong Lu. 6454-6465 [doi]
• A/B Testing for Recommender Systems in a Two-sided MarketplacePreetam Nandy, Divya Venugopalan, Chun Lo, Shaunak Chatterjee. 6466-6477 [doi]
• Retiring Adult: New Datasets for Fair Machine LearningFrances Ding, Moritz Hardt, John Miller 0001, Ludwig Schmidt. 6478-6490 [doi]
• Cardinality constrained submodular maximization for random streamsPaul Liu, Aviad Rubinstein, Jan Vondrák, Junyao Zhao 0001. 6491-6502 [doi]
• Self-Instantiated Recurrent Units with Dynamic Soft RecursionAston Zhang, Yi Tay, Yikang Shen, Alvin Chan, Shuai Zhang 0007. 6503-6514 [doi]
• Sparse Uncertainty Representation in Deep Learning with Inducing WeightsHippolyt Ritter, Martin Kukla, Cheng Zhang 0005, Yingzhen Li. 6515-6528 [doi]
• Scalable Inference of Sparsely-changing Gaussian Markov Random FieldsSalar Fattahi, Andrés Gómez 0001. 6529-6541 [doi]
• Grad2Task: Improved Few-shot Text Classification Using Gradients for Task RepresentationJixuan Wang, Kuan-Chieh Wang, Frank Rudzicz, Michael Brudno. 6542-6554 [doi]
• Learnability of Linear Thresholds from Label ProportionsRishi Saket. 6555-6566 [doi]
• A variational approximate posterior for the deep Wishart processSebastian W. Ober, Laurence Aitchison. 6567-6579 [doi]
• Neural Pseudo-Label Optimism for the Bank Loan ProblemAldo Pacchiano, Shaun Singh, Edward Chou, Alexander C. Berg, Jakob N. Foerster. 6580-6593 [doi]
• Visualizing the Emergence of Intermediate Visual Patterns in DNNsMingjie Li, Shaobo Wang, Quanshi Zhang. 6594-6607 [doi]
• Learning 3D Dense Correspondence via Canonical Point AutoencoderAn-Chieh Cheng, Xueting Li, Min Sun, Ming-Hsuan Yang 0001, Sifei Liu. 6608-6620 [doi]
• Speech-T: Transducer for Text to Speech and BeyondJiawei Chen 0008, Xu Tan 0003, Yichong Leng, Jin Xu 0010, Guihua Wen, Tao Qin, Tie-Yan Liu. 6621-6633 [doi]
• Multi-modal Dependency Tree for Video CaptioningWentian Zhao, Xinxiao Wu, Jiebo Luo. 6634-6645 [doi]
• Greedy and Random Quasi-Newton Methods with Faster Explicit Superlinear ConvergenceDachao Lin, Haishan Ye, Zhihua Zhang. 6646-6657 [doi]
• Neural Tangent Kernel Maximum Mean DiscrepancyXiuyuan Cheng, Yao Xie 0002. 6658-6670 [doi]
• Subgraph Federated Learning with Missing Neighbor GenerationKe Zhang, Carl Yang, Xiaoxiao Li, Lichao Sun, Siu-Ming Yiu. 6671-6682 [doi]
• Bellman-consistent Pessimism for Offline Reinforcement LearningTengyang Xie, Ching-An Cheng, Nan Jiang 0008, Paul Mineiro, Alekh Agarwal. 6683-6694 [doi]
• Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent NetworksAvi Schwarzschild, Eitan Borgnia, Arjun Gupta, Furong Huang, Uzi Vishkin, Micah Goldblum, Tom Goldstein. 6695-6706 [doi]
• Sub-Linear Memory: How to Make Performers SLiMValerii Likhosherstov, Krzysztof Marcin Choromanski, Jared Quincy Davis, Xingyou Song, Adrian Weller. 6707-6719 [doi]
• Efficient Learning of Discrete-Continuous Computation GraphsDavid Friede, Mathias Niepert. 6720-6732 [doi]
• VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector QuantizationMucong Ding, Kezhi Kong, Jingling Li, Chen Zhu, John Dickerson 0001, Furong Huang, Tom Goldstein. 6733-6746 [doi]
• Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat MinimaGuangyuan Shi, Jiaxin Chen, Wenlong Zhang, Li-Ming Zhan, Xiao-Ming Wu 0003. 6747-6761 [doi]
• Functional Neural Networks for Parametric Image Restoration ProblemsFangzhou Luo, Xiaolin Wu 0001, Yanhui Guo. 6762-6775 [doi]
• Intrinsic Dimension, Persistent Homology and Generalization in Neural NetworksTolga Birdal, Aaron Lou, Leonidas J. Guibas, Umut Simsekli. 6776-6789 [doi]
• GemNet: Universal Directional Graph Neural Networks for MoleculesJohannes Gasteiger, Florian Becker, Stephan Günnemann. 6790-6802 [doi]
• Loss function based second-order Jensen inequality and its application to particle variational inferenceFutoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama. 6803-6815 [doi]
• Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online LearningAodong Li, Alex Boyd, Padhraic Smyth, Stephan Mandt. 6816-6828 [doi]
• Asynchronous Decentralized SGD with Quantized and Local UpdatesGiorgi Nadiradze, Amirmojtaba Sabour, Peter Davies, Shigang Li 0002, Dan Alistarh. 6829-6842 [doi]
• Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free RegretJean Tarbouriech, Runlong Zhou, Simon S. Du, Matteo Pirotta, Michal Valko, Alessandro Lazaric. 6843-6855 [doi]
• Nested Counterfactual Identification from Arbitrary Surrogate ExperimentsJuan D. Correa, Sanghack Lee, Elias Bareinboim. 6856-6867 [doi]
• Sim and Real: Better TogetherShirli Di-Castro Shashua, Dotan Di Castro, Shie Mannor. 6868-6880 [doi]
• Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma DistributionsHuan Ma, Zongbo Han, Changqing Zhang, Huazhu Fu, Joey Tianyi Zhou, Qinghua Hu. 6881-6893 [doi]
• An Empirical Study of Adder Neural Networks for Object DetectionXinghao Chen 0001, Chang Xu 0002, Minjing Dong, Chunjing Xu, Yunhe Wang 0001. 6894-6905 [doi]
• Does Knowledge Distillation Really Work?Samuel Stanton, Pavel Izmailov, Polina Kirichenko, Alexander A. Alemi, Andrew Gordon Wilson. 6906-6919 [doi]
• Teachable Reinforcement Learning via Advice DistillationOlivia Watkins, Abhishek Gupta 0004, Trevor Darrell, Pieter Abbeel, Jacob Andreas. 6920-6933 [doi]
• Antipodes of Label Differential Privacy: PATE and ALIBIMani Malek Esmaeili, Ilya Mironov, Karthik Prasad, Igor Shilov, Florian Tramèr. 6934-6945 [doi]
• Visual Search Asymmetry: Deep Nets and Humans Share Similar Inherent BiasesShashi Kant Gupta, Mengmi Zhang, Chia-Chien Wu, Jeremy M. Wolfe, Gabriel Kreiman. 6946-6959 [doi]
• On the Universality of Graph Neural Networks on Large Random GraphsNicolas Keriven, Alberto Bietti, Samuel Vaiter. 6960-6971 [doi]
• Inverse Reinforcement Learning in a Continuous State Space with Formal GuaranteesGregory Dexter, Kevin Bello, Jean Honorio. 6972-6982 [doi]
• Adversarial Attacks on Graph Classifiers via Bayesian OptimisationXingchen Wan, Henry Kenlay, Robin Ru, Arno Blaas, Michael A. Osborne, Xiaowen Dong 0001. 6983-6996 [doi]
• Regulating algorithmic filtering on social mediaSarah Huiyi Cen, Devavrat Shah. 6997-7011 [doi]
• argmax centroidChengYue Gong, Mao Ye, Qiang Liu 0001. 7012-7024 [doi]
• Contrastive Learning of Global and Local Video RepresentationsShuang Ma, Zhaoyang Zeng, Daniel McDuff, Yale Song. 7025-7040 [doi]
• BooVI: Provably Efficient Bootstrapped Value IterationBoyi Liu, Qi Cai, Zhuoran Yang, Zhaoran Wang. 7041-7053 [doi]
• Do Wider Neural Networks Really Help Adversarial Robustness?Boxi Wu, Jinghui Chen, Deng Cai 0001, Xiaofei He 0001, Quanquan Gu. 7054-7067 [doi]
• Exploring the Limits of Out-of-Distribution DetectionStanislav Fort, Jie Ren 0006, Balaji Lakshminarayanan. 7068-7081 [doi]
• ABC: Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised LearningHyuck Lee, SeungJae Shin, Heeyoung Kim. 7082-7094 [doi]
• BCD Nets: Scalable Variational Approaches for Bayesian Causal DiscoveryChris Cundy, Aditya Grover, Stefano Ermon. 7095-7110 [doi]
• Discovering Dynamic Salient Regions for Spatio-Temporal Graph Neural NetworksIulia Duta, Andrei Liviu Nicolicioiu, Marius Leordeanu. 7111-7125 [doi]
• Information-constrained optimization: can adaptive processing of gradients help?Jayadev Acharya, Clément L. Canonne, Prathamesh Mayekar, Himanshu Tyagi. 7126-7138 [doi]
• Towards Calibrated Model for Long-Tailed Visual Recognition from Prior PerspectiveZhengzhuo Xu, Zenghao Chai, Chun Yuan. 7139-7152 [doi]
• Learning to Draw: Emergent Communication through SketchingDaniela Mihai, Jonathon S. Hare. 7153-7166 [doi]
• Self-Supervised Learning of Event-Based Optical Flow with Spiking Neural NetworksJesse J. Hagenaars, Federico Paredes-Vallés, Guido de Croon. 7167-7179 [doi]
• On the Value of Infinite Gradients in Variational Autoencoder ModelsBin Dai, Wenliang Li, David P. Wipf. 7180-7192 [doi]
• Online Robust Reinforcement Learning with Model UncertaintyYue Wang,