Table of Contents

• A New Representation of Successor Features for Transfer across Dissimilar EnvironmentsMajid Abdolshah, Hung Le, Thommen George Karimpanal, Sunil Gupta 0001, Santu Rana, Svetha Venkatesh. 1-9 [doi]
• Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time ScalingKuruge Darshana Abeyrathna, Bimal Bhattarai, Morten Goodwin, Saeed Rahimi Gorji, Ole-Christoffer Granmo, Lei Jiao, Rupsa Saha, Rohan Kumar Yadav. 10-20 [doi]
• Debiasing Model Updates for Improving Personalized Federated TrainingDurmus Alp Emre Acar, Yue Zhao, Ruizhao Zhu, Ramon Matas Navarro, Matthew Mattina, Paul N. Whatmough, Venkatesh Saligrama. 21-31 [doi]
• Memory Efficient Online Meta LearningDurmus Alp Emre Acar, Ruizhao Zhu, Venkatesh Saligrama. 32-42 [doi]
• Robust Testing and Estimation under Manipulation AttacksJayadev Acharya, Ziteng Sun, Huanyu Zhang. 43-53 [doi]
• GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental LearningIdan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya. 54-65 [doi]
• f-Domain Adversarial Learning: Theory and AlgorithmsDavid Acuna, Guojun Zhang, Marc T. Law, Sanja Fidler. 66-75 [doi]
• Towards Rigorous Interpretations: a Formalisation of Feature AttributionDarius Afchar, Vincent Guigue, Romain Hennequin. 76-86 [doi]
• Acceleration via Fractal Learning Rate SchedulesNaman Agarwal, Surbhi Goel, Cyril Zhang. 87-99 [doi]
• A Regret Minimization Approach to Iterative Learning ControlNaman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh. 100-109 [doi]
• Towards the Unification and Robustness of Perturbation and Gradient Based ExplanationsSushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu 0001, Himabindu Lakkaraju. 110-119 [doi]
• Label Inference Attacks from Log-loss ScoresAbhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier. 120-129 [doi]
• Deep Kernel ProcessesLaurence Aitchison, Adam X. Yang, Sebastian W. Ober. 130-140 [doi]
• How Does Loss Function Affect Generalization Performance of Deep Learning? Application to Human Age EstimationAli Akbari, Muhammad Awais 0001, Manijeh Bashar, Josef Kittler. 141-151 [doi]
• On Learnability via Gradient Method for Two-Layer ReLU Neural Networks in Teacher-Student SettingShunta Akiyama, Taiji Suzuki. 152-162 [doi]
• Slot Machines: Discovering Winning Combinations of Random Weights in Neural NetworksMaxwell Mbabilla Aladago, Lorenzo Torresani. 163-174 [doi]
• A large-scale benchmark for few-shot program induction and synthesisFerran Alet, Javier Lopez-Contreras, James Koppel, Maxwell I. Nye, Armando Solar-Lezama, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Joshua B. Tenenbaum. 175-186 [doi]
• Robust Pure Exploration in Linear Bandits with Limited BudgetAyya Alieva, Ashok Cutkosky, Abhimanyu Das. 187-195 [doi]
• Communication-Efficient Distributed Optimization with Quantized PreconditionersFoivos Alimisis, Peter Davies, Dan Alistarh. 196-206 [doi]
• Non-Exponentially Weighted Aggregation: Regret Bounds for Unbounded Loss FunctionsPierre Alquier. 207-218 [doi]
• Dataset Dynamics via Gradient Flows in Probability SpaceDavid Alvarez-Melis, Nicolò Fusi. 219-230 [doi]
• Submodular Maximization subject to a Knapsack Constraint: Combinatorial Algorithms with Near-optimal Adaptive ComplexityGeorgios Amanatidis, Federico Fusco, Philip Lazos, Stefano Leonardi, Alberto Marchetti-Spaccamela, Rebecca Reiffenhäuser. 231-242 [doi]
• Safe Reinforcement Learning with Linear Function ApproximationSanae Amani, Christos Thrampoulidis, Lin Yang 0011. 243-253 [doi]
• Automatic variational inference with cascading flowsLuca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven. 254-263 [doi]
• Sparse Bayesian Learning via Stepwise RegressionSebastian E. Ament, Carla P. Gomes. 264-274 [doi]
• Locally Persistent Exploration in Continuous Control Tasks with Sparse RewardsSusan Amin, Maziar Gomrokchi, Hossein Aboutalebi, Harsh Satija, Doina Precup. 275-285 [doi]
• Preferential Temporal Difference LearningNishanth V. Anand, Doina Precup. 286-296 [doi]
• Unitary Branching Programs: Learnability and Lower BoundsFidel Ernesto Diaz Andino, Maria Kokkou, Mateus de Oliveira Oliveira, Farhad Vadiee. 297-306 [doi]
• The Logical Options FrameworkBrandon Araki, Xiao Li 0025, Kiran Vodrahalli, Jonathan A. DeCastro, Micah J. Fry, Daniela Rus. 307-317 [doi]
• Annealed Flow Transport Monte CarloMichael Arbel, Alexander G. de G. Matthews, Arnaud Doucet. 318-330 [doi]
• Permutation WeightingDavid Arbour, Drew Dimmery, Arjun Sondhi. 331-341 [doi]
• Analyzing the tree-layer structure of Deep ForestsLudovic Arnould, Claire Boyer, Erwan Scornet. 342-350 [doi]
• Dropout: Explicit Forms and Capacity ControlRaman Arora, Peter Bartlett, Poorya Mianjy, Nathan Srebro. 351-361 [doi]
• Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate GradientsArtem Artemev, David R. Burt, Mark van der Wilk. 362-372 [doi]
• Deciding What to Learn: A Rate-Distortion ApproachDilip Arumugam, Benjamin Van Roy. 373-382 [doi]
• Private Adaptive Gradient Methods for Convex OptimizationHilal Asi, John C. Duchi, Alireza Fallah 0001, Omid Javidbakht, Kunal Talwar. 383-392 [doi]
• Private Stochastic Convex Optimization: Optimal Rates in L1 GeometryHilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar. 393-403 [doi]
• Combinatorial Blocking Bandits with Stochastic DelaysAlexia Atsidakou, Orestis Papadigenopoulos, Soumya Basu 0001, Constantine Caramanis, Sanjay Shakkottai. 404-413 [doi]
• Dichotomous Optimistic Search to Quantify Human PerceptionJulien Audiffren. 414-424 [doi]
• Federated Learning under Arbitrary Communication PatternsDmitrii Avdiukhin, Shiva Prasad Kasiviswanathan. 425-435 [doi]
• Asynchronous Distributed Learning : Adapting to Gradient Delays without Prior KnowledgeRotem Zamir Aviv, Ido Hakimi, Assaf Schuster, Kfir Yehuda Levy. 436-445 [doi]
• Decomposable Submodular Function Minimization via Maximum FlowKyriakos Axiotis, Adam Karczmarz, Anish Mukherjee 0001, Piotr Sankowski, Adrian Vladu. 446-456 [doi]
• Differentially Private Query Release Through Adaptive ProjectionSergül Aydöre, William Brown, Michael Kearns, Krishnaram Kenthapadi, Luca Melis, Aaron Roth 0001, Ankit A. Siva. 457-467 [doi]
• On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror DescentShahar Azulay, Edward Moroshko, Mor Shpigel Nacson, Blake E. Woodworth, Nathan Srebro, Amir Globerson, Daniel Soudry. 468-477 [doi]
• On-Off Center-Surround Receptive Fields for Accurate and Robust Image ClassificationZahra Babaiee, Ramin M. Hasani, Mathias Lechner, Daniela Rus, Radu Grosu. 478-489 [doi]
• Uniform Convergence, Adversarial Spheres and a Simple RemedyGregor Bachmann, Seyed-Mohsen Moosavi-Dezfooli, Thomas Hofmann. 490-499 [doi]
• Faster Kernel Matrix Algebra via Density EstimationArturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner. 500-510 [doi]
• Robust Reinforcement Learning using Least Squares Policy Iteration with Provable Performance GuaranteesKishan Panaganti Badrinath, Dileep Kalathil. 511-520 [doi]
• Skill Discovery for Exploration and Planning using Deep Skill GraphsAkhil Bagaria, Jason K. Senthil, George Konidaris 0001. 521-531 [doi]
• Locally Adaptive Label Smoothing Improves Predictive ChurnDara Bahri, Heinrich Jiang. 532-542 [doi]
• How Important is the Train-Validation Split in Meta-Learning?Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason D. Lee, Sham M. Kakade, Huan Wang, Caiming Xiong. 543-553 [doi]
• Stabilizing Equilibrium Models by Jacobian RegularizationShaojie Bai, Vladlen Koltun, J. Zico Kolter. 554-565 [doi]
• Don't Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary ClassificationYu Bai, Song Mei, Huan Wang, Caiming Xiong. 566-576 [doi]
• Principled Exploration via Optimistic Bootstrapping and Backward InductionChenjia Bai, Lingxiao Wang, Lei Han, Jianye Hao, Animesh Garg, Peng Liu 0008, Zhaoran Wang. 577-587 [doi]
• GLSearch: Maximum Common Subgraph Detection via Learning to SearchYunsheng Bai, Derek Xu, Yizhou Sun, Wei Wang 0010. 588-598 [doi]
• Breaking the Limits of Message Passing Graph Neural NetworksMuhammet Balcilar, Pierre Héroux, Benoit Gaüzère, Pascal Vasseur, Sébastien Adam, Paul Honeine. 599-608 [doi]
• Instance Specific Approximations for Submodular MaximizationEric Balkanski, Sharon Qian, Yaron Singer. 609-618 [doi]
• Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline EnvironmentPhilip J. Ball, Cong Lu, Jack Parker-Holder, Stephen J. Roberts. 619-629 [doi]
• Regularized Online Allocation Problems: Fairness and BeyondSantiago R. Balseiro, Haihao Lu, Vahab S. Mirrokni. 630-639 [doi]
• Predict then Interpolate: A Simple Algorithm to Learn Stable ClassifiersYujia Bao, Shiyu Chang, Regina Barzilay. 640-650 [doi]
• Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable ModelsFan Bao, Kun Xu 0004, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang 0010. 651-661 [doi]
• Compositional Video Synthesis with Action GraphsAmir Bar, Roei Herzig, Xiaolong Wang 0004, Anna Rohrbach, Gal Chechik, Trevor Darrell, Amir Globerson. 662-673 [doi]
• Approximating a Distribution Using Weight QueriesNadav Barak, Sivan Sabato. 674-683 [doi]
• Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution GeneralizationAseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath. 684-693 [doi]
• Training Quantized Neural Networks to Global Optimality via Semidefinite ProgrammingBurak Bartan, Mert Pilanci. 694-704 [doi]
• 2(T) regret for decentralized bandits in matching marketsSoumya Basu 0001, Karthik Abinav Sankararaman, Abishek Sankararaman. 705-715 [doi]
• Optimal Thompson Sampling strategies for support-aware CVaR banditsDorian Baudry, Romain Gautron, Emilie Kaufmann, Odalric Maillard. 716-726 [doi]
• On Limited-Memory Subsampling Strategies for BanditsDorian Baudry, Yoan Russac, Olivier Cappé. 727-737 [doi]
• Generalized Doubly Reparameterized Gradient EstimatorsMatthias Bauer, Andriy Mnih. 738-747 [doi]
• Directional Graph NetworksDominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Lió. 748-758 [doi]
• Policy Analysis using Synthetic Controls in Continuous-TimeAlexis Bellot, Mihaela van der Schaar. 759-768 [doi]
• Loss Surface Simplexes for Mode Connecting Volumes and Fast EnsemblingGregory W. Benton, Wesley Maddox, Sanae Lotfi, Andrew Gordon Wilson. 769-779 [doi]
• TFix: Learning to Fix Coding Errors with a Text-to-Text TransformerBerkay Berabi, Jingxuan He, Veselin Raychev, Martin T. Vechev. 780-791 [doi]
• Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival AnalysisJeroen Berrevoets, Ahmed M. Alaa, Zhaozhi Qian, James Jordon, Alexander E. S. Gimson, Mihaela van der Schaar. 792-802 [doi]
• Learning from Biased Data: A Semi-Parametric ApproachPatrice Bertail, Stéphan Clémençon, Yannick Guyonvarch, Nathan Noiry. 803-812 [doi]
• Is Space-Time Attention All You Need for Video Understanding?Gedas Bertasius, Heng Wang, Lorenzo Torresani. 813-824 [doi]
• Confidence Scores Make Instance-dependent Label-noise Learning PossibleAntonin Berthon, Bo Han 0003, Gang Niu 0001, Tongliang Liu, Masashi Sugiyama. 825-836 [doi]
• Size-Invariant Graph Representations for Graph Classification ExtrapolationsBeatrice Bevilacqua, Yangze Zhou, Bruno Ribeiro 0001. 837-851 [doi]
• Principal Bit Analysis: Autoencoding with Schur-Concave LossSourbh Bhadane, Aaron B. Wagner, Jayadev Acharya. 852-862 [doi]
• Lower Bounds on Cross-Entropy Loss in the Presence of Test-time AdversariesArjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal. 863-873 [doi]
• Additive Error Guarantees for Weighted Low Rank ApproximationAditya Bhaskara, Aravinda Kanchana Ruwanpathirana, Maheshakya Wijewardena. 874-883 [doi]
• Sample Complexity of Robust Linear Classification on Separated DataRobi Bhattacharjee, Somesh Jha, Kamalika Chaudhuri. 884-893 [doi]
• Finding k in Latent k- polytopeChiranjib Bhattacharyya, Ravindran Kannan, Amit Kumar 0001. 894-903 [doi]
• Non-Autoregressive Electron Redistribution Modeling for Reaction PredictionHangrui Bi, Hengyi Wang, Chence Shi, Connor W. Coley, Jian Tang 0005, Hongyu Guo. 904-913 [doi]
• TempoRL: Learning When to ActAndré Biedenkapp, Raghu Rajan, Frank Hutter, Marius Lindauer. 914-924 [doi]
• Follow-the-Regularized-Leader Routes to Chaos in Routing GamesJakub Bielawski, Thiparat Chotibut, Fryderyk Falniowski, Grzegorz Kosiorowski, Michal Misiurewicz, Georgios Piliouras. 925-935 [doi]
• Neural Symbolic Regression that scalesLuca Biggio, Tommaso Bendinelli, Alexander Neitz, Aurélien Lucchi, Giambattista Parascandolo. 936-945 [doi]
• Model Distillation for Revenue Optimization: Interpretable Personalized PricingMax Biggs, Wei Sun 0031, Markus Ettl. 946-956 [doi]
• Scalable Normalizing Flows for Permutation Invariant DensitiesMarin Bilos, Stephan Günnemann. 957-967 [doi]
• Online Learning for Load Balancing of Unknown Monotone Resource Allocation GamesIlai Bistritz, Nicholas Bambos. 968-979 [doi]
• Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half PrecisionJohan Björck, Xiangyu Chen, Christopher De Sa, Carla P. Gomes, Kilian Q. Weinberger. 980-991 [doi]
• Multiplying Matrices Without MultiplyingDavis W. Blalock, John V. Guttag. 992-1004 [doi]
• One for One, or All for All: Equilibria and Optimality of Collaboration in Federated LearningAvrim Blum, Nika Haghtalab, Richard Lanas Phillips, Han Shao. 1005-1014 [doi]
• Black-box density function estimation using recursive partitioningErik Bodin, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek. 1015-1025 [doi]
• Weisfeiler and Lehman Go Topological: Message Passing Simplicial NetworksCristian Bodnar, Fabrizio Frasca, Yuguang Wang 0001, Nina Otter, Guido F. Montúfar, Pietro Lió, Michael M. Bronstein. 1026-1037 [doi]
• The Hintons in your Neural Network: a Quantum Field Theory View of Deep LearningRoberto Bondesan, Max Welling. 1038-1048 [doi]
• Offline Contextual Bandits with Overparameterized ModelsDavid Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna. 1049-1058 [doi]
• High-Performance Large-Scale Image Recognition Without NormalizationAndy Brock, Soham De, Samuel L. Smith, Karen Simonyan. 1059-1071 [doi]
• Evaluating the Implicit Midpoint Integrator for Riemannian Hamiltonian Monte CarloJames A. Brofos, Roy R. Lederman. 1072-1081 [doi]
• Reinforcement Learning of Implicit and Explicit Control Flow InstructionsEthan A. Brooks, Janarthanan Rajendran, Richard L. Lewis, Satinder Singh. 1082-1091 [doi]
• Machine Unlearning for Random ForestsJonathan Brophy, Daniel Lowd. 1092-1104 [doi]
• Value Alignment VerificationDaniel S. Brown, Jordan Schneider, Anca D. Dragan, Scott Niekum. 1105-1115 [doi]
• Model-Free and Model-Based Policy Evaluation when Causality is UncertainDavid Bruns-Smith. 1116-1126 [doi]
• Narrow Margins: Classification, Margins and Fat TailsFrancois Buet-Golfouse. 1127-1135 [doi]
• Differentially Private Correlation ClusteringMark Bun, Marek Eliás 0001, Janardhan Kulkarni. 1136-1146 [doi]
• Disambiguation of Weak Supervision leading to Exponential Convergence ratesVivien A. Cabannnes, Francis R. Bach, Alessandro Rudi. 1147-1157 [doi]
• Finite mixture models do not reliably learn the number of componentsDiana Cai, Trevor Campbell, Tamara Broderick. 1158-1169 [doi]
• A Theory of Label Propagation for Subpopulation ShiftTianle Cai, RuiQi Gao, Jason Lee, Qi Lei. 1170-1182 [doi]
• Lenient Regret and Good-Action Identification in Gaussian Process BanditsXu Cai, Selwyn Gomes, Jonathan Scarlett. 1183-1192 [doi]
• A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box OptimizationHanQin Cai, Yuchen Lou, Daniel McKenzie, Wotao Yin. 1193-1203 [doi]
• GraphNorm: A Principled Approach to Accelerating Graph Neural Network TrainingTianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang 0001. 1204-1215 [doi]
• On Lower Bounds for Standard and Robust Gaussian Process Bandit OptimizationXu Cai, Jonathan Scarlett. 1216-1226 [doi]
• High-dimensional Experimental Design and Kernel BanditsRomain Camilleri, Kevin Jamieson, Julian Katz-Samuels. 1227-1237 [doi]
• A Gradient Based Strategy for Hamiltonian Monte Carlo Hyperparameter OptimizationAndrew Campbell, Wenlong Chen, Vincent Stimper, José Miguel Hernández-Lobato, Yichuan Zhang. 1238-1248 [doi]
• Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise InjectionsAlexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris C. Holmes, Mert Gürbüzbalaban, Umut Simsekli. 1249-1260 [doi]
• Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein DesignYue Cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen. 1261-1271 [doi]
• Learning from Similarity-Confidence DataYuzhou Cao, Lei Feng, Yitian Xu, Bo An 0001, Gang Niu 0001, Masashi Sugiyama. 1272-1282 [doi]
• Parameter-free Locally Accelerated Conditional GradientsAlejandro Carderera, Jelena Diakonikolas, Cheuk Yin Lin, Sebastian Pokutta. 1283-1293 [doi]
• Optimizing persistent homology based functionsMathieu Carrière, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan, Yuhei Umeda. 1294-1303 [doi]
• Online Policy Gradient for Model Free Learning of Linear Quadratic Regulators with √T RegretAsaf Cassel, Tomer Koren. 1304-1313 [doi]
• Multi-Receiver Online Bayesian PersuasionMatteo Castiglioni, Alberto Marchesi, Andrea Celli, Nicola Gatti 0001. 1314-1323 [doi]
• Marginal Contribution Feature Importance - an Axiomatic Approach for Explaining DataAmnon Catav, Boyang Fu, Yazeed Zoabi, Ahuva Weiss-Meilik, Noam Shomron, Jason Ernst, Sriram Sankararaman, Ran Gilad-Bachrach. 1324-1335 [doi]
• Disentangling syntax and semantics in the brain with deep networksCharlotte Caucheteux, Alexandre Gramfort, Jean-Remi King. 1336-1348 [doi]
• Fair Classification with Noisy Protected Attributes: A Framework with Provable GuaranteesL. Elisa Celis, Lingxiao Huang, Vijay Keswani, Nisheeth K. Vishnoi. 1349-1361 [doi]
• Best Model Identification: A Rested Bandit FormulationLeonardo Cella, Massimiliano Pontil, Claudio Gentile. 1362-1372 [doi]
• Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning researchJohan Samir Obando-Ceron, Pablo Samuel Castro. 1373-1383 [doi]
• Learning Routines for Effective Off-Policy Reinforcement LearningEdoardo Cetin, Oya Çeliktutan. 1384-1394 [doi]
• Learning Node Representations Using Stationary Flow Prediction on Large Payment and Cash Transaction NetworksCiwan Ceylan, Salla Franzén, Florian T. Pokorny. 1395-1406 [doi]
• GRAND: Graph Neural DiffusionBen Chamberlain 0001, James Rowbottom, Maria Gorinova, Michael M. Bronstein, Stefan Webb, Emanuele Rossi. 1407-1418 [doi]
• HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical ProjectionsInes Chami, Albert Gu, Dat Nguyen, Christopher Ré. 1419-1429 [doi]
• Goal-Conditioned Reinforcement Learning with Imagined SubgoalsElliot Chane-Sane, Cordelia Schmid, Ivan Laptev. 1430-1440 [doi]
• Locally Private k-Means in One RoundAlisa Chang, Badih Ghazi, Ravi Kumar 0001, Pasin Manurangsi. 1441-1451 [doi]
• Modularity in Reinforcement Learning via Algorithmic Independence in Credit AssignmentMichael Chang 0003, Sidhant Kaushik, Sergey Levine, Tom Griffiths. 1452-1462 [doi]
• Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed DetectionNadine Chang, Zhiding Yu, Yu-Xiong Wang, Animashree Anandkumar, Sanja Fidler, Jose M. Alvarez. 1463-1472 [doi]
• DeepWalking Backwards: From Embeddings Back to GraphsSudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis. 1473-1483 [doi]
• Differentiable Spatial Planning using TransformersDevendra Singh Chaplot, Deepak Pathak, Jitendra Malik. 1484-1495 [doi]
• Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement LearningHenry Charlesworth, Giovanni Montana. 1496-1506 [doi]
• Classification with Rejection Based on Cost-sensitive ClassificationNontawat Charoenphakdee, Zhenghang Cui, Yivan Zhang, Masashi Sugiyama. 1507-1517 [doi]
• Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic SkillsYevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jacob Varley, Alex Irpan, Benjamin Eysenbach, Ryan Julian, Chelsea Finn, Sergey Levine. 1518-1528 [doi]
• Unified Robust Semi-Supervised Variational AutoencoderXu Chen. 1529-1538 [doi]
• Unsupervised Learning of Visual 3D Keypoints for ControlBoyuan Chen, Pieter Abbeel, Deepak Pathak. 1539-1549 [doi]
• Integer Programming for Causal Structure Learning in the Presence of Latent VariablesRui Chen, Sanjeeb Dash, Tian Gao. 1550-1560 [doi]
• Improved Corruption Robust Algorithms for Episodic Reinforcement LearningYifang Chen, Simon S. Du, Kevin Jamieson. 1561-1570 [doi]
• Scalable Computations of Wasserstein Barycenter via Input Convex Neural NetworksYongxin Chen, JiaoJiao Fan, Amirhossein Taghvaei. 1571-1581 [doi]
• Neural Feature Matching in Implicit 3D RepresentationsYunlu Chen, Basura Fernando, Hakan Bilen, Thomas Mensink, Efstratios Gavves. 1582-1593 [doi]
• Decentralized Riemannian Gradient Descent on the Stiefel ManifoldShixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour. 1594-1605 [doi]
• Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential RecommendationChao Chen, Haoyu Geng, Nianzu Yang, Junchi Yan, Daiyue Xue, Jianping Yu, Xiaokang Yang. 1606-1616 [doi]
• Mandoline: Model Evaluation under Distribution ShiftMayee F. Chen, Karan Goel, Nimit Sharad Sohoni, Fait Poms, Kayvon Fatahalian, Christopher Ré. 1617-1629 [doi]
• Order Matters: Probabilistic Modeling of Node Sequence for Graph GenerationXiaohui Chen, Xu Han, Jiajing Hu, Francisco J. R. Ruiz, Li-Ping Liu. 1630-1639 [doi]
• CARTL: Cooperative Adversarially-Robust Transfer LearningDian Chen 0004, Hongxin Hu, Qian Wang 0002, Yinli Li, Cong Wang 0001, Chao Shen, Qi Li 0002. 1640-1650 [doi]
• Finding the Stochastic Shortest Path with Low Regret: the Adversarial Cost and Unknown Transition CaseLiyu Chen, Haipeng Luo. 1651-1660 [doi]
• SpreadsheetCoder: Formula Prediction from Semi-structured ContextXinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou. 1661-1672 [doi]
• Large-Margin Contrastive Learning with Distance Polarization RegularizerShuo Chen 0003, Gang Niu 0001, Chen Gong 0002, Jun Li, Jian Yang, Masashi Sugiyama. 1673-1683 [doi]
• Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series ForecastingYuzhou Chen, Ignacio Segovia-Dominguez, Yulia R. Gel. 1684-1694 [doi]
• A Unified Lottery Ticket Hypothesis for Graph Neural NetworksTianlong Chen, Yongduo Sui, Xuxi Chen, Aston Zhang, Zhangyang Wang. 1695-1706 [doi]
• Network Inference and Influence Maximization from SamplesWei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang. 1707-1716 [doi]
• Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic MapsRenyi Chen, Molei Tao. 1717-1727 [doi]
• Analysis of stochastic Lanczos quadrature for spectrum approximationTyler Chen, Thomas Trogdon, Shashanka Ubaru. 1728-1739 [doi]
• Large-Scale Multi-Agent Deep FBSDEsTianrong Chen, Ziyi Wang, Ioannis Exarchos, Evangelos A. Theodorou. 1740-1748 [doi]
• Representation Subspace Distance for Domain Adaptation RegressionXinyang Chen, Sinan Wang, Jianmin Wang, Mingsheng Long. 1749-1759 [doi]
• Overcoming Catastrophic Forgetting by Bayesian Generative RegularizationPei-Hung Chen, Wei Wei 0025, Cho-Jui Hsieh, Bo Dai. 1760-1770 [doi]
• Cyclically Equivariant Neural Decoders for Cyclic CodesXiangyu Chen, Min Ye. 1771-1780 [doi]
• A Receptor Skeleton for Capsule Neural NetworksJintai Chen, Hongyun Yu, Chengde Qian, Danny Z. Chen, Jian Wu 0001. 1781-1790 [doi]
• Accelerating Gossip SGD with Periodic Global AveragingYiming Chen 0003, Kun Yuan, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin. 1791-1802 [doi]
• ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed TrainingJianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael W. Mahoney, Joseph Gonzalez 0001. 1803-1813 [doi]
• SPADE: A Spectral Method for Black-Box Adversarial Robustness EvaluationWuxinlin Cheng, Chenhui Deng, Zhiqiang Zhao, Yaohui Cai, Zhiru Zhang, Zhuo Feng. 1814-1824 [doi]
• Self-supervised and Supervised Joint Training for Resource-rich Machine TranslationYong Cheng, Wei Wang, Lu Jiang, Wolfgang Macherey. 1825-1835 [doi]
• Exact Optimization of Conformal Predictors via Incremental and Decremental LearningGiovanni Cherubin, Konstantinos Chatzikokolakis 0001, Martin Jaggi. 1836-1845 [doi]
• Problem Dependent View on Structured Thresholding Bandit ProblemsJames Cheshire, Pierre Ménard, Alexandra Carpentier. 1846-1854 [doi]
• Online Optimization in Games via Control Theory: Connecting Regret, Passivity and Poincaré RecurrenceYun Kuen Cheung, Georgios Piliouras. 1855-1865 [doi]
• Understanding and Mitigating Accuracy Disparity in RegressionJianfeng Chi, Yuan Tian 0001, Geoffrey J. Gordon, Han Zhao 0002. 1866-1876 [doi]
• Private Alternating Least Squares: Practical Private Matrix Completion with Tighter RatesSteve Chien, Prateek Jain 0002, Walid Krichene, Steffen Rendle, Shuang Song 0001, Abhradeep Thakurta, Li Zhang 0069. 1877-1887 [doi]
• Light RUMsFlavio Chierichetti, Ravi Kumar 0001, Andrew Tomkins. 1888-1897 [doi]
• Parallelizing Legendre Memory Unit TrainingNarsimha Reddy Chilkuri, Chris Eliasmith. 1898-1907 [doi]
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• Fairness and Bias in Online SelectionJosé R. Correa, Andrés Cristi, Paul Duetting, Ashkan Norouzi-Fard. 2112-2121 [doi]
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• Characterizing Fairness Over the Set of Good Models Under Selective LabelsAmanda Coston, Ashesh Rambachan, Alexandra Chouldechova. 2144-2155 [doi]
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• 1-APGD for Sparse Adversarial Attacks on Image ClassifiersFrancesco Croce, Matthias Hein 0001. 2201-2211 [doi]
• Parameterless Transductive Feature Re-representation for Few-Shot LearningWentao Cui, Yuhong Guo. 2212-2221 [doi]
• Randomized Algorithms for Submodular Function Maximization with a k-System ConstraintShuang Cui, Kai Han 0003, Tianshuai Zhu, Jing Tang 0004, Benwei Wu, He Huang 0001. 2222-2232 [doi]
• GBHT: Gradient Boosting Histogram Transform for Density EstimationJingyi Cui, Hanyuan Hang, Yisen Wang 0001, Zhouchen Lin. 2233-2243 [doi]
• ProGraML: A Graph-based Program Representation for Data Flow Analysis and Compiler OptimizationsChris Cummins, Zacharias V. Fisches, Tal Ben-Nun, Torsten Hoefler, Michael F. P. O'Boyle, Hugh Leather. 2244-2253 [doi]
• Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement LearningSebastian Curi, Ilija Bogunovic, Andreas Krause 0001. 2254-2264 [doi]
• Quantifying Availability and Discovery in Recommender Systems via Stochastic ReachabilityMihaela Curmei, Sarah Dean, Benjamin Recht. 2265-2275 [doi]
• Dynamic Balancing for Model Selection in Bandits and RLAshok Cutkosky, Christoph Dann, Abhimanyu Das, Claudio Gentile, Aldo Pacchiano, Manish Purohit. 2276-2285 [doi]
• ConViT: Improving Vision Transformers with Soft Convolutional Inductive BiasesStéphane d'Ascoli, Hugo Touvron, Matthew L. Leavitt, Ari S. Morcos, Giulio Biroli, Levent Sagun. 2286-2296 [doi]
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• Convex Regularization in Monte-Carlo Tree SearchTuan Dam, Carlo D'Eramo, Jan Peters 0001, Joni Pajarinen. 2365-2375 [doi]
• Demonstration-Conditioned Reinforcement Learning for Few-Shot ImitationChristopher R. Dance, Julien Perez, Théo Cachet. 2376-2387 [doi]
• Re-understanding Finite-State Representations of Recurrent Policy NetworksMohamad H. Danesh, Anurag Koul, Alan Fern, Saeed Khorram. 2388-2397 [doi]
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• Catformer: Designing Stable Transformers via Sensitivity AnalysisJared Quincy Davis, Albert Gu, Krzysztof Choromanski, Tri Dao, Christopher Ré, Chelsea Finn, Percy Liang. 2489-2499 [doi]
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• High-Dimensional Gaussian Process Inference with DerivativesFilip de Roos, Alexandra Gessner, Philipp Hennig. 2535-2545 [doi]
• Transfer-Based Semantic Anomaly DetectionLucas Deecke, Lukas Ruff, Robert A. Vandermeulen, Hakan Bilen. 2546-2558 [doi]
• Grid-Functioned Neural NetworksJavier Dehesa, Andrew Vidler, Julian A. Padget, Christof Lutteroth. 2559-2567 [doi]
• Multidimensional Scaling: Approximation and ComplexityErik D. Demaine, Adam Hesterberg, Frederic Koehler, Jayson Lynch, John Urschel. 2568-2578 [doi]
• What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?Weijian Deng, Stephen Gould, Liang Zheng 0001. 2579-2589 [doi]
• Toward Better Generalization Bounds with Locally Elastic StabilityZhun Deng, Hangfeng He, Weijie J. Su. 2590-2600 [doi]
• Revenue-Incentive Tradeoffs in Dynamic Reserve PricingYuan Deng, Sébastien Lahaie, Vahab S. Mirrokni, Song Zuo. 2601-2610 [doi]
• Heterogeneity for the Win: One-Shot Federated ClusteringDon Kurian Dennis, Tian Li 0005, Virginia Smith. 2611-2620 [doi]
• Kernel Continual LearningMohammad Mahdi Derakhshani, Xiantong Zhen, Ling Shao 0001, Cees Snoek. 2621-2631 [doi]
• Bayesian Optimization over Hybrid SpacesAryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa. 2632-2643 [doi]
• Navigation Turing Test (NTT): Learning to Evaluate Human-Like NavigationSam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann. 2644-2653 [doi]
• Versatile Verification of Tree EnsemblesLaurens Devos, Wannes Meert, Jesse Davis. 2654-2664 [doi]
• On the Inherent Regularization Effects of Noise Injection During TrainingOussama Dhifallah, Yue M. Lu. 2665-2675 [doi]
• Hierarchical Agglomerative Graph Clustering in Nearly-Linear TimeLaxman Dhulipala, David Eisenstat, Jakub Lacki, Vahab S. Mirrokni, Jessica Shi. 2676-2686 [doi]
• Learning Online Algorithms with Distributional AdviceIlias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Ali Vakilian, Nikos Zarifis. 2687-2696 [doi]
• A Wasserstein Minimax Framework for Mixed Linear RegressionTheo Diamandis, Yonina C. Eldar, Alireza Fallah 0001, Farzan Farnia, Asuman E. Ozdaglar. 2697-2706 [doi]
• Context-Aware Online Collective Inference for Templated Graphical ModelsCharles Dickens, Connor Pryor, Eriq Augustine, Alexander Miller, Lise Getoor. 2707-2716 [doi]
• ARMS: Antithetic-REINFORCE-Multi-Sample Gradient for Binary VariablesAleksandar Dimitriev, Mingyuan Zhou. 2717-2727 [doi]
• XOR-CD: Linearly Convergent Constrained Structure GenerationFan Ding, Jianzhu Ma, Jinbo Xu, Yexiang Xue. 2728-2738 [doi]
• Dual Principal Component Pursuit for Robust Subspace Learning: Theory and Algorithms for a Holistic ApproachTianyu Ding, Zhihui Zhu, René Vidal, Daniel P. Robinson. 2739-2748 [doi]
• Coded-InvNet for Resilient Prediction Serving SystemsTuan Dinh, Kangwook Lee 0001. 2749-2759 [doi]
• Estimation and Quantization of Expected Persistence DiagramsVincent Divol, Théo Lacombe. 2760-2770 [doi]
• On Energy-Based Models with Overparametrized Shallow Neural NetworksCarles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden, Joan Bruna. 2771-2782 [doi]
• Kernel-Based Reinforcement Learning: A Finite-Time AnalysisOmar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Emilie Kaufmann, Michal Valko. 2783-2792 [doi]
• Attention is not all you need: pure attention loses rank doubly exponentially with depthYihe Dong, Jean-Baptiste Cordonnier, Andreas Loukas. 2793-2803 [doi]
• How rotational invariance of common kernels prevents generalization in high dimensionsKonstantin Donhauser, Mingqi Wu, Fanny Yang. 2804-2814 [doi]
• Fast Stochastic Bregman Gradient Methods: Sharp Analysis and Variance ReductionRadu-Alexandru Dragomir, Mathieu Even, Hadrien Hendrikx. 2815-2825 [doi]
• Bilinear Classes: A Structural Framework for Provable Generalization in RLSimon S. Du, Sham M. Kakade, Jason D. Lee, Shachar Lovett, Gaurav Mahajan, Wen Sun, Ruosong Wang. 2826-2836 [doi]
• Improved Contrastive Divergence Training of Energy-Based ModelsYilun Du, Shuang Li, Joshua B. Tenenbaum, Igor Mordatch. 2837-2848 [doi]
• Order-Agnostic Cross Entropy for Non-Autoregressive Machine TranslationCunxiao Du, Zhaopeng Tu, Jing Jiang. 2849-2859 [doi]
• Putting the "Learning" into Learning-Augmented Algorithms for Frequency EstimationElbert Du, Franklyn Wang, Michael Mitzenmacher. 2860-2869 [doi]
• Estimating α-Rank from A Few Entries with Low Rank Matrix CompletionYali Du, Xue Yan, Xu Chen, Jun Wang, Haifeng Zhang. 2870-2879 [doi]
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• Provably Strict Generalisation Benefit for Equivariant ModelsBryn Elesedy, Sheheryar Zaidi. 2959-2969 [doi]
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• Implicit Bias of Linear RNNsMelikasadat Emami, Mojtaba Sahraee-Ardakan, Parthe Pandit, Sundeep Rangan, Alyson K. Fletcher. 2982-2992 [doi]
• Global Optimality Beyond Two Layers: Training Deep ReLU Networks via Convex ProgramsTolga Ergen, Mert Pilanci. 2993-3003 [doi]
• Revealing the Structure of Deep Neural Networks via Convex DualityTolga Ergen, Mert Pilanci. 3004-3014 [doi]
• Whitening for Self-Supervised Representation LearningAleksandr Ermolov, Aliaksandr Siarohin, Enver Sangineto, Nicu Sebe. 3015-3024 [doi]
• Graph Mixture Density NetworksFederico Errica, Davide Bacciu, Alessio Micheli. 3025-3035 [doi]
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• Weight-covariance alignment for adversarially robust neural networksPanagiotis Eustratiadis, Henry Gouk, Da Li, Timothy M. Hospedales. 3047-3056 [doi]
• Data augmentation for deep learning based accelerated MRI reconstruction with limited dataZalan Fabian, Reinhard Heckel, Mahdi Soltanolkotabi. 3057-3067 [doi]
• Poisson-Randomised DirBN: Large Mutation is Needed in Dirichlet Belief NetworksXuhui Fan, Bin Li, Yaqiong Li, Scott A. Sisson. 3068-3077 [doi]
• Model-based Reinforcement Learning for Continuous Control with Posterior SamplingYing Fan, Yifei Ming. 3078-3087 [doi]
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• On Estimation in Latent Variable ModelsGuanhua Fang, Ping Li 0001. 3100-3110 [doi]
• On Variational Inference in Biclustering ModelsGuanhua Fang, Ping Li 0001. 3111-3121 [doi]
• Learning Bounds for Open-Set LearningZhen Fang, Jie Lu, Anjin Liu, Feng Liu, Guangquan Zhang 0001. 3122-3132 [doi]
• Streaming Bayesian Deep Tensor FactorizationShikai Fang, Zheng Wang, Zhimeng Pan, Ji Liu, Shandian Zhe. 3133-3142 [doi]
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• Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential NoiseVivek F. Farias, Andrew A. Li, Tianyi Peng. 3154-3163 [doi]
• Connecting Optimal Ex-Ante Collusion in Teams to Extensive-Form Correlation: Faster Algorithms and Positive Complexity ResultsGabriele Farina, Andrea Celli, Nicola Gatti 0001, Tuomas Sandholm. 3164-3173 [doi]
• Train simultaneously, generalize better: Stability of gradient-based minimax learnersFarzan Farnia, Asuman E. Ozdaglar. 3174-3185 [doi]
• Unbalanced minibatch Optimal Transport; applications to Domain AdaptationKilian Fatras, Thibault Séjourné, Rémi Flamary, Nicolas Courty. 3186-3197 [doi]
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• Reserve Price Optimization for First Price Auctions in Display AdvertisingZhe Feng 0004, Sébastien Lahaie, Jon Schneider, Jinchao Ye. 3230-3239 [doi]
• Uncertainty Principles of Encoding GANsRuili Feng, Zhouchen Lin, Jiapeng Zhu, Deli Zhao, Jingren Zhou, Zheng-Jun Zha. 3240-3251 [doi]
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• Provably Correct Optimization and Exploration with Non-linear PoliciesFei Feng, Wotao Yin, Alekh Agarwal, Lin Yang 0011. 3263-3273 [doi]
• KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge DistillationHaozhe Feng, Zhaoyang You, Minghao Chen, Tianye Zhang, Minfeng Zhu, Fei Wu, Chao Wu, Wei Chen. 3274-3283 [doi]
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• Scalable Certified Segmentation via Randomized SmoothingMarc Fischer, Maximilian Baader, Martin T. Vechev. 3340-3351 [doi]
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• Online A-Optimal Design and Active Linear RegressionXavier Fontaine, Pierre Perrault, Michal Valko, Vianney Perchet. 3374-3383 [doi]
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• Post-selection inference with HSIC-LassoTobias Freidling, Benjamin Poignard, Héctor Climente-González, Makoto Yamada. 3439-3448 [doi]
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• Let's Agree to Degree: Comparing Graph Convolutional Networks in the Message-Passing FrameworkFloris Geerts, Filip Mazowiecki, Guillermo A. Pérez 0001. 3640-3649 [doi]
• On the difficulty of unbiased alpha divergence minimizationTomas Geffner, Justin Domke. 3650-3659 [doi]
• How and Why to Use Experimental Data to Evaluate Methods for Observational Causal InferenceAmanda Gentzel, Purva Pruthi, David Jensen. 3660-3671 [doi]
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• 12-Lead ECG Reconstruction via Koopman OperatorsTomer Golany, Kira Radinsky, Daniel Freedman, Saar Minha. 3745-3754 [doi]
• Function Contrastive Learning of Transferable Meta-RepresentationsMuhammad Waleed Gondal, Shruti Joshi, Nasim Rahaman, Stefan Bauer, Manuel Wuthrich, Bernhard Schölkopf. 3755-3765 [doi]
• Active Slices for Sliced Stein DiscrepancyWenbo Gong 0001, Kaibo Zhang, Yingzhen Li, José Miguel Hernández-Lobato. 3766-3776 [doi]
• On the Problem of Underranking in Group-Fair RankingSruthi Gorantla, Amit Deshpande, Anand Louis. 3777-3787 [doi]
• MARINA: Faster Non-Convex Distributed Learning with CompressionEduard A. Gorbunov, Konstantin Burlachenko, Zhize Li, Peter Richtárik. 3788-3798 [doi]
• Systematic Analysis of Cluster Similarity Indices: How to Validate Validation MeasuresMartijn Gösgens, Alexey Tikhonov, Liudmila Prokhorenkova. 3799-3808 [doi]
• Revisiting Point Cloud Shape Classification with a Simple and Effective BaselineAnkit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng 0001. 3809-3820 [doi]
• Dissecting Supervised Constrastive LearningFlorian Graf, Christoph D. Hofer, Marc Niethammer, Roland Kwitt. 3821-3830 [doi]
• Oops I Took A Gradient: Scalable Sampling for Discrete DistributionsWill Grathwohl, Kevin Swersky, Milad Hashemi, David Duvenaud, Chris J. Maddison. 3831-3841 [doi]
• Detecting Rewards Deterioration in Episodic Reinforcement LearningIdo Greenberg, Shie Mannor. 3842-3853 [doi]
• Crystallization Learning with the Delaunay TriangulationJiaqi Gu, Guosheng Yin. 3854-3863 [doi]
• AutoAttend: Automated Attention Representation SearchChaoyu Guan, Xin Wang, Wenwu Zhu 0001. 3864-3874 [doi]
• Operationalizing Complex Causes: A Pragmatic View of MediationLimor Gultchin, David S. Watson, Matt J. Kusner, Ricardo Silva. 3875-3885 [doi]
• On a Combination of Alternating Minimization and Nesterov's MomentumSergey Guminov, Pavel E. Dvurechensky, Nazarii Tupitsa, Alexander V. Gasnikov. 3886-3898 [doi]
• Decentralized Single-Timescale Actor-Critic on Zero-Sum Two-Player Stochastic GamesHongyi Guo, Zuyue Fu, Zhuoran Yang, Zhaoran Wang. 3899-3909 [doi]
• Adversarial Policy Learning in Two-player Competitive GamesWenbo Guo 0002, Xian Wu, Sui Huang, Xinyu Xing. 3910-3919 [doi]
• Soft then Hard: Rethinking the Quantization in Neural Image CompressionZongyu Guo, Zhizheng Zhang, Runsen Feng, Zhibo Chen 0001. 3920-3929 [doi]
• UneVEn: Universal Value Exploration for Multi-Agent Reinforcement LearningTarun Gupta 0002, Anuj Mahajan, Bei Peng, Wendelin Boehmer, Shimon Whiteson. 3930-3941 [doi]
• Distribution-Free Calibration Guarantees for Histogram Binning without Sample SplittingChirag Gupta, Aaditya Ramdas. 3942-3952 [doi]
• Correcting Exposure Bias for Link RecommendationShantanu Gupta, Hao Wang, Zachary Lipton, Yuyang Wang. 3953-3963 [doi]
• The Heavy-Tail Phenomenon in SGDMert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu. 3964-3975 [doi]
• Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial AttacksNezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang 0001, Bo Li. 3976-3987 [doi]
• Adapting to Delays and Data in Adversarial Multi-Armed BanditsAndrás György 0001, Pooria Joulani. 3988-3997 [doi]
• Rate-Distortion Analysis of Minimum Excess Risk in Bayesian LearningHassan Hafez-Kolahi, Behrad Moniri, Shohreh Kasaei, Mahdieh Soleymani Baghshah. 3998-4007 [doi]
• Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient ApproachNadav Hallak, Panayotis Mertikopoulos, Volkan Cevher. 4008-4017 [doi]
• Diversity Actor-Critic: Sample-Aware Entropy Regularization for Sample-Efficient ExplorationSeungyul Han, Youngchul Sung. 4018-4029 [doi]
• Adversarial Combinatorial Bandits with General Non-linear Reward FunctionsYanjun Han, Yining Wang, Xi Chen. 4030-4039 [doi]
• A Collective Learning Framework to Boost GNN Expressiveness for Node ClassificationMengyue Hang, Jennifer Neville, Bruno Ribeiro 0001. 4040-4050 [doi]
• Grounding Language to Entities and Dynamics for Generalization in Reinforcement LearningAustin W. Hanjie, Victor Zhong, Karthik Narasimhan. 4051-4062 [doi]
• Sparse Feature Selection Makes Batch Reinforcement Learning More Sample EfficientBotao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvári, Mengdi Wang. 4063-4073 [doi]
• Bootstrapping Fitted Q-Evaluation for Off-Policy InferenceBotao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvári, Mengdi Wang. 4074-4084 [doi]
• Compressed Maximum LikelihoodYi Hao, Alon Orlitsky. 4085-4095 [doi]
• Valid Causal Inference with (Some) Invalid InstrumentsJason S. Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown. 4096-4106 [doi]
• Model Performance Scaling with Multiple Data SourcesTatsunori Hashimoto. 4107-4116 [doi]
• Hierarchical VAEs Know What They Don't KnowJakob Drachmann Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe. 4117-4128 [doi]
• Defense against backdoor attacks via robust covariance estimationJonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh. 4129-4139 [doi]
• Boosting for Online Convex OptimizationElad Hazan, Karan Singh. 4140-4149 [doi]
• PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale ModelsChaoyang He 0001, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr. 4150-4159 [doi]
• SoundDet: Polyphonic Moving Sound Event Detection and Localization from Raw WaveformYuhang He, Niki Trigoni, Andrew Markham. 4160-4170 [doi]
• Logarithmic Regret for Reinforcement Learning with Linear Function ApproximationJiafan He, Dongruo Zhou, Quanquan Gu. 4171-4180 [doi]
• Finding Relevant Information via a Discrete Fourier ExpansionMohsen Heidari, Jithin K. Sreedharan, Gil I. Shamir, Wojciech Szpankowski. 4181-4191 [doi]
• Zeroth-Order Non-Convex Learning via Hierarchical Dual AveragingAmélie Héliou, Matthieu Martin, Panayotis Mertikopoulos, Thibaud Rahier. 4192-4202 [doi]
• Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced SparsityRyan Henderson, Djork-Arné Clevert, Floriane Montanari. 4203-4213 [doi]
• Muesli: Combining Improvements in Policy OptimizationMatteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado van Hasselt. 4214-4226 [doi]
• Learning Representations by Humans, for HumansSophie Hilgard, Nir Rosenfeld, Mahzarin R. Banaji, Jack Cao, David C. Parkes. 4227-4238 [doi]
• Optimizing Black-box Metrics with Iterative Example WeightingGaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Mahdi Milani Fard, Sanmi Koyejo. 4239-4249 [doi]
• Trees with Attention for Set Prediction TasksRoy Hirsch, Ran Gilad-Bachrach. 4250-4261 [doi]
• Multiplicative Noise and Heavy Tails in Stochastic OptimizationLiam Hodgkinson, Michael W. Mahoney. 4262-4274 [doi]
• MC-LSTM: Mass-Conserving LSTMPieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz, Christina Halmich, Markus Holzleitner, Grey Nearing, Sepp Hochreiter, Günter Klambauer. 4275-4286 [doi]
• Learning Curves for Analysis of Deep NetworksDerek Hoiem, Tanmay Gupta, Zhizhong Li 0001, Michal Shlapentokh-Rothman. 4287-4296 [doi]
• Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural ProcessesPeter Holderrieth, Michael Hutchinson, Yee Whye Teh. 4297-4307 [doi]
• Latent Programmer: Discrete Latent Codes for Program SynthesisJoey Hong, David Dohan, Rishabh Singh, Charles Sutton, Manzil Zaheer. 4308-4318 [doi]
• Chebyshev Polynomial Codes: Task Entanglement-based Coding for Distributed Matrix MultiplicationSangwoo Hong, Heecheol Yang, YoungSeok Yoon, Taehyun Cho, Jungwoo Lee 0001. 4319-4327 [doi]
• Federated Learning of User Verification Models Without Sharing EmbeddingsHossein Hosseini, Hyunsin Park, Sungrack Yun, Christos Louizos, Joseph Soriaga, Max Welling. 4328-4336 [doi]
• The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical SetsYa-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher. 4337-4348 [doi]
• Near-Optimal Representation Learning for Linear Bandits and Linear RLJiachen Hu, Xiaoyu Chen, Chi Jin, Lihong Li, Liwei Wang 0001. 4349-4358 [doi]
• On the Random Conjugate Kernel and Neural Tangent KernelZhengmian Hu, Heng Huang. 4359-4368 [doi]
• Off-Belief LearningHengyuan Hu, Adam Lerer, Brandon Cui, Luis-Pineda, Noam Brown, Jakob N. Foerster. 4369-4379 [doi]
• Generalizable Episodic Memory for Deep Reinforcement LearningHao Hu, Jianing Ye, Guangxiang Zhu, Zhizhou Ren, Chongjie Zhang. 4380-4390 [doi]
• A Scalable Deterministic Global Optimization Algorithm for Clustering ProblemsKaixun Hua, Mingfei Shi, Yankai Cao. 4391-4401 [doi]
• On Recovering from Modeling Errors Using Testing Bayesian NetworksHaiying Huang, Adnan Darwiche. 4402-4411 [doi]
• A Novel Sequential Coreset Method for Gradient Descent AlgorithmsJiawei Huang, Ruomin Huang, Wenjie Liu, Nikolaos M. Freris, Hu Ding. 4412-4422 [doi]
• FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning AnalysisBaihe Huang, Xiaoxiao Li, Zhao Song 0002, Xin Yang 0017. 4423-4434 [doi]
• STRODE: Stochastic Boundary Ordinary Differential EquationHengguan Huang, Hongfu Liu, Hao Wang 0014, Chang Xiao, Ye Wang. 4435-4445 [doi]
• A Riemannian Block Coordinate Descent Method for Computing the Projection Robust Wasserstein DistanceMinhui Huang, Shiqian Ma, Lifeng Lai. 4446-4455 [doi]
• Projection Robust Wasserstein BarycentersMinhui Huang, Shiqian Ma, Lifeng Lai. 4456-4465 [doi]
• Accurate Post Training Quantization With Small Calibration SetsItay Hubara, Yury Nahshan, Yair Hanani, Ron Banner, Daniel Soudry. 4466-4475 [doi]
• Learning and Planning in Complex Action SpacesThomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Mohammadamin Barekatain, Simon Schmitt, David Silver. 4476-4486 [doi]
• Generative Adversarial TransformersDrew A. Hudson, Larry Zitnick. 4487-4499 [doi]
• Neural Pharmacodynamic State Space ModelingZeshan Hussain, Rahul G. Krishnan, David Sontag. 4500-4510 [doi]
• Hyperparameter Selection for Imitation LearningLéonard Hussenot, Marcin Andrychowicz, Damien Vincent, Robert Dadashi, Anton Raichuk, Sabela Ramos, Nikola Momchev, Sertan Girgin, Raphaël Marinier, Lukasz Stafiniak, Manu Orsini, Olivier Bachem, Matthieu Geist, Olivier Pietquin. 4511-4522 [doi]
• Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed DistributionsTodd Huster, Jeremy E. J. Cohen, Zinan Lin 0001, Kevin Chan, Charles A. Kamhoua, Nandi O. Leslie, Cho-Yu Jason Chiang, Vyas Sekar. 4523-4532 [doi]
• LieTransformer: Equivariant Self-Attention for Lie GroupsMichael Hutchinson, Charline Le Lan, Sheheryar Zaidi, Emilien Dupont, Yee Whye Teh, Hyunjik Kim. 4533-4543 [doi]
• Crowdsourcing via Annotator Co-occurrence Imputation and Provable Symmetric Nonnegative Matrix FactorizationShahana Ibrahim, Xiao Fu 0001. 4544-4554 [doi]
• Selecting Data Augmentation for Simulating InterventionsMaximilian Ilse, Jakub M. Tomczak, Patrick Forré. 4555-4562 [doi]
• Scalable Marginal Likelihood Estimation for Model Selection in Deep LearningAlexander Immer, Matthias Bauer, Vincent Fortuin, Gunnar Rätsch, Mohammad Emtiyaz Khan. 4563-4573 [doi]
• Active Learning for Distributionally Robust Level-Set EstimationYu Inatsu, Shogo Iwazaki, Ichiro Takeuchi. 4574-4584 [doi]
• Learning Randomly Perturbed Structured Predictors for Direct Loss MinimizationHedda Cohen Indelman, Tamir Hazan. 4585-4595 [doi]
• Randomized Entity-wise Factorization for Multi-Agent Reinforcement LearningShariq Iqbal, Christian A. Schröder de Witt, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha. 4596-4606 [doi]
• Randomized Exploration in Reinforcement Learning with General Value Function ApproximationHaque Ishfaq, Qiwen Cui, Viet Nguyen, Alex Ayoub, Zhuoran Yang, Zhaoran Wang, Doina Precup, Lin Yang. 4607-4616 [doi]
• Distributed Second Order Methods with Fast Rates and Compressed CommunicationRustem Islamov, Xun Qian, Peter Richtárik. 4617-4628 [doi]
• What Are Bayesian Neural Network Posteriors Really Like?Pavel Izmailov, Sharad Vikram, Matthew D. Hoffman, Andrew Gordon Wilson. 4629-4640 [doi]
• How to Learn when Data Reacts to Your Model: Performative Gradient DescentZachary Izzo, Lexing Ying, James Zou 0001. 4641-4650 [doi]
• Perceiver: General Perception with Iterative AttentionAndrew Jaegle, Felix Gimeno, Andy Brock, Oriol Vinyals, Andrew Zisserman, João Carreira. 4651-4664 [doi]
• Imitation by Predicting ObservationsAndrew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Greg Wayne. 4665-4676 [doi]
• Local Correlation Clustering with Asymmetric Classification ErrorsJafar Jafarov, Sanchit Kalhan, Konstantin Makarychev, Yury Makarychev. 4677-4686 [doi]
• Alternative Microfoundations for Strategic ClassificationMeena Jagadeesan, Celestine Mendler-Dünner, Moritz Hardt. 4687-4697 [doi]
• Robust Density Estimation from Batches: The Best Things in Life are (Nearly) FreeAyush Jain, Alon Orlitsky. 4698-4708 [doi]
• Instance-Optimal Compressed Sensing via Posterior SamplingAjil Jalal, Sushrut Karmalkar, Alex Dimakis, Eric Price. 4709-4720 [doi]
• Fairness for Image Generation with Uncertain Sensitive AttributesAjil Jalal, Sushrut Karmalkar, Jessica Hoffmann, Alex Dimakis, Eric Price. 4721-4732 [doi]
• Feature Clustering for Support Identification in Extreme RegionsHamid Jalalzai, Rémi Leluc. 4733-4743 [doi]
• Improved Regret Bounds of Bilinear Bandits using Action Space AnalysisKyoungseok Jang, Kwang-Sung Jun, Se-Young Yun, Wanmo Kang. 4744-4754 [doi]
• Inverse Decision Modeling: Learning Interpretable Representations of BehaviorDaniel Jarrett, Alihan Hüyük, Mihaela van der Schaar. 4755-4771 [doi]
• Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts GeneralizationStanislaw Jastrzebski, Devansh Arpit, Oliver Åstrand, Giancarlo Kerg, Huan Wang, Caiming Xiong, Richard Socher, KyungHyun Cho, Krzysztof J. Geras. 4772-4784 [doi]
• Policy Gradient Bayesian Robust Optimization for Imitation LearningZaynah Javed, Daniel S. Brown, Satvik Sharma, Jerry Zhu, Ashwin Balakrishna, Marek Petrik, Anca D. Dragan, Ken Goldberg. 4785-4796 [doi]
• In-Database Regression in Input Sparsity TimeRajesh Jayaram, Alireza Samadian, David P. Woodruff, Peng Ye 0005. 4797-4806 [doi]
• Parallel and Flexible Sampling from Autoregressive Models via Langevin DynamicsVivek Jayaram, John Thickstun. 4807-4818 [doi]
• Objective Bound Conditional Gaussian Process for Bayesian OptimizationTaewon Jeong, Heeyoung Kim. 4819-4828 [doi]
• Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden ConfoundingAndrew Jesson, Sören Mindermann, Yarin Gal, Uri Shalit. 4829-4838 [doi]
• DeepReDuce: ReLU Reduction for Fast Private InferenceNandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen. 4839-4849 [doi]
• Factor-analytic inverse regression for high-dimension, small-sample dimensionality reductionAditi Jha, Michael J. Morais, Jonathan W. Pillow. 4850-4859 [doi]
• Fast margin maximization via dual accelerationZiwei Ji, Nathan Srebro, Matus Telgarsky. 4860-4869 [doi]
• Marginalized Stochastic Natural Gradients for Black-Box Variational InferenceGeng Ji 0001, Debora Sujono, Erik B. Sudderth. 4870-4881 [doi]
• Bilevel Optimization: Convergence Analysis and Enhanced DesignKaiyi Ji, Junjie Yang, Yingbin Liang. 4882-4892 [doi]
• Efficient Statistical Tests: A Neural Tangent Kernel ApproachSheng Jia, Ehsan Nezhadarya, Yuhuai Wu, Jimmy Ba. 4893-4903 [doi]
• Scaling Up Visual and Vision-Language Representation Learning With Noisy Text SupervisionChao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc V. Le, Yun-Hsuan Sung, Zhen Li, Tom Duerig. 4904-4916 [doi]
• Multi-Dimensional Classification via Sparse Label EncodingBin-Bin Jia, Min-Ling Zhang. 4917-4926 [doi]
• Self-Damaging Contrastive LearningZiyu Jiang, Tianlong Chen, Bobak J. Mortazavi, Zhangyang Wang. 4927-4939 [doi]
• Prioritized Level ReplayMinqi Jiang, Edward Grefenstette, Tim Rocktäschel. 4940-4950 [doi]
• Monotonic Robust Policy Optimization with Model DiscrepancyYuankun Jiang, Chenglin Li, Wenrui Dai, Junni Zou, Hongkai Xiong. 4951-4960 [doi]
• Approximation Theory of Convolutional Architectures for Time Series ModellingHaotian Jiang, Zhong Li, Qianxiao Li. 4961-4970 [doi]
• Streaming and Distributed Algorithms for Robust Column Subset SelectionShuli Jiang, Dennis Li, Irene Mengze Li, Arvind V. Mahankali, David P. Woodruff. 4971-4981 [doi]
• Single Pass Entrywise-Transformed Low Rank ApproximationYifei Jiang, Yi Li, Yiming Sun, Jiaxin Wang, David P. Woodruff. 4982-4991 [doi]
• The Emergence of IndividualityJiechuan Jiang, Zongqing Lu. 4992-5001 [doi]
• Online Selection Problems against Constrained AdversaryZhihao Jiang, Pinyan Lu, Zhihao Gavin Tang, Yuhao Zhang 0001. 5002-5012 [doi]
• Active CoveringHeinrich Jiang, Afshin Rostamizadeh. 5013-5022 [doi]
• Emphatic Algorithms for Deep Reinforcement LearningRay Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado van Hasselt. 5023-5033 [doi]
• Characterizing Structural Regularities of Labeled Data in Overparameterized ModelsZiheng Jiang, Chiyuan Zhang, Kunal Talwar, Michael C. Mozer. 5034-5044 [doi]
• Optimal Streaming Algorithms for Multi-Armed BanditsTianyuan Jin, Keke Huang, Jing Tang 0004, Xiaokui Xiao. 5045-5054 [doi]
• Towards Tight Bounds on the Sample Complexity of Average-reward MDPsYujia Jin, Aaron Sidford. 5055-5064 [doi]
• Almost Optimal Anytime Algorithm for Batched Multi-Armed BanditsTianyuan Jin, Jing Tang 0004, Pan Xu 0002, Keke Huang, Xiaokui Xiao, Quanquan Gu. 5065-5073 [doi]
• MOTS: Minimax Optimal Thompson SamplingTianyuan Jin, Pan Xu 0002, Jieming Shi, Xiaokui Xiao, Quanquan Gu. 5074-5083 [doi]
• Is Pessimism Provably Efficient for Offline RL?Ying Jin, Zhuoran Yang, Zhaoran Wang. 5084-5096 [doi]
• Adversarial Option-Aware Hierarchical Imitation LearningMingxuan Jing, Wenbing Huang, Fuchun Sun 0001, Xiaojian Ma, Tao Kong, Chuang Gan, Lei Li. 5097-5106 [doi]
• Discrete-Valued Latent Preference Matrix Estimation with Graph Side InformationChanghun Jo, Kangwook Lee 0001. 5107-5117 [doi]
• Provable Lipschitz Certification for Generative ModelsMatt Jordan, Alex Dimakis. 5118-5126 [doi]
• Isometric Gaussian Process Latent Variable Model for Dissimilarity DataMartin Jørgensen, Søren Hauberg. 5127-5136 [doi]
• On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel ModelsPeizhong Ju, Xiaojun Lin, Ness B. Shroff. 5137-5147 [doi]
• Improved Confidence Bounds for the Linear Logistic Model and Applications to BanditsKwang-Sung Jun, Lalit Jain, Houssam Nassif, Blake Mason. 5148-5157 [doi]
• Detection of Signal in the Spiked Rectangular ModelsJi Hyung Jung, Hye Won Chung, Ji Oon Lee. 5158-5167 [doi]
• Estimating Identifiable Causal Effects on Markov Equivalence Class through Double Machine LearningYonghan Jung, Jin Tian 0001, Elias Bareinboim. 5168-5179 [doi]
• A Nullspace Property for Subspace-Preserving RecoveryMustafa Devrim Kaba, Chong You, Daniel P. Robinson, Enrique Mallada, René Vidal. 5180-5188 [doi]
• Training Recurrent Neural Networks via Forward Propagation Through TimeAnil Kag, Venkatesh Saligrama. 5189-5200 [doi]
• The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure AggregationPeter Kairouz, Ziyu Liu, Thomas Steinke 0002. 5201-5212 [doi]
• Practical and Private (Deep) Learning Without Sampling or ShufflingPeter Kairouz, Brendan McMahan, Shuang Song 0001, Om Thakkar 0001, Abhradeep Thakurta, Zheng Xu. 5213-5225 [doi]
• A Differentiable Point Process with Its Application to Spiking Neural NetworksHiroshi Kajino. 5226-5235 [doi]
• Projection techniques to update the truncated SVD of evolving matrices with applicationsVasileios Kalantzis, Georgios Kollias, Shashanka Ubaru, Athanasios N. Nikolakopoulos, Lior Horesh, Kenneth L. Clarkson. 5236-5246 [doi]
• Optimal Off-Policy Evaluation from Multiple Logging PoliciesNathan Kallus, Yuta Saito, Masatoshi Uehara. 5247-5256 [doi]
• Efficient Performance Bounds for Primal-Dual Reinforcement Learning from DemonstrationsAngeliki Kamoutsi, Goran Banjac, John Lygeros. 5257-5268 [doi]
• Statistical Estimation from Dependent DataVardis Vardis Kandiros, Yuval Dagan, Nishanth Dikkala, Surbhi Goel, Constantinos Daskalakis. 5269-5278 [doi]
• SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian ProcessesSanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson. 5279-5289 [doi]
• Variational Auto-Regressive Gaussian Processes for Continual LearningSanyam Kapoor, Theofanis Karaletsos, Thang D. Bui. 5290-5300 [doi]
• Off-Policy Confidence SequencesNikos Karampatziakis, Paul Mineiro, Aaditya Ramdas. 5301-5310 [doi]
• Learning from History for Byzantine Robust OptimizationSai Praneeth Karimireddy, Lie He, Martin Jaggi. 5311-5319 [doi]
• Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio EstimationMasahiro Kato, Takeshi Teshima. 5320-5333 [doi]
• Improved Algorithms for Agnostic Pool-based Active ClassificationJulian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson. 5334-5344 [doi]
• When Does Data Augmentation Help With Membership Inference Attacks?Yigitcan Kaya, Tudor Dumitras. 5345-5355 [doi]
• Regularized Submodular Maximization at ScaleEhsan Kazemi 0001, Shervin Minaee, Moran Feldman, Amin Karbasi. 5356-5366 [doi]
• Prior Image-Constrained Reconstruction using Style-Based Generative ModelsVarun A. Kelkar, Mark A. Anastasio. 5367-5377 [doi]
• Self Normalizing FlowsT. Anderson Keller, Jorn W. T. Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling. 5378-5387 [doi]
• Interpretable Stability Bounds for Spectral Graph FiltersHenry Kenlay, Dorina Thanou, Xiaowen Dong 0001. 5388-5397 [doi]
• Affine Invariant Analysis of Frank-Wolfe on Strongly Convex SetsThomas Kerdreux, Lewis Liu, Simon Lacoste-Julien, Damien Scieur. 5398-5408 [doi]
• Markpainting: Adversarial Machine Learning meets InpaintingDavid Khachaturov, Ilia Shumailov, Yiren Zhao, Nicolas Papernot, Ross J. Anderson. 5409-5419 [doi]
• Finite-Sample Analysis of Off-Policy Natural Actor-Critic AlgorithmSajad Khodadadian, Zaiwei Chen, Siva Theja Maguluri. 5420-5431 [doi]
• Functional Space Analysis of Local GAN ConvergenceValentin Khrulkov, Artem Babenko, Ivan V. Oseledets. 5432-5442 [doi]
• "Hey, that's not an ODE": Faster ODE Adjoints via SeminormsPatrick Kidger, Ricky T. Q. Chen, Terry J. Lyons. 5443-5452 [doi]
• Neural SDEs as Infinite-Dimensional GANsPatrick Kidger, James Foster, Xuechen Li, Terry J. Lyons. 5453-5463 [doi]
• GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model TrainingKrishnaTeja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan, Abir De, Rishabh K. Iyer. 5464-5474 [doi]
• Improving Predictors via Combination Across Diverse Task CategoriesKwang In Kim. 5475-5485 [doi]
• Self-Improved Retrosynthetic PlanningJunsu Kim, Sungsoo Ahn, Hankook Lee, Jinwoo Shin. 5486-5495 [doi]
• Reward Identification in Inverse Reinforcement LearningKuno Kim, Shivam Garg, Kirankumar Shiragur, Stefano Ermon. 5496-5505 [doi]
• I-BERT: Integer-only BERT QuantizationSehoon Kim, Amir Gholami, Zhewei Yao, Michael W. Mahoney, Kurt Keutzer. 5506-5518 [doi]
• Message Passing Adaptive Resonance Theory for Online Active Semi-supervised LearningTaeHyeong Kim, Injune Hwang, Hyundo Lee, Hyunseo Kim, Won-Seok Choi, Joseph J. Lim, Byoung-Tak Zhang. 5519-5529 [doi]
• Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-SpeechJaehyeon Kim, Jungil Kong, Juhee Son. 5530-5540 [doi]
• A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement LearningDong Ki Kim, Miao Liu 0001, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan P. How. 5541-5550 [doi]
• Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential EquationsTimothy D. Kim, Thomas Z. Luo, Jonathan W. Pillow, Carlos Brody. 5551-5561 [doi]
• The Lipschitz Constant of Self-AttentionHyunjik Kim, George Papamakarios, Andriy Mnih. 5562-5571 [doi]
• Unsupervised Skill Discovery with Bottleneck Option LearningJaekyeom Kim, Seohong Park, Gunhee Kim. 5572-5582 [doi]
• ViLT: Vision-and-Language Transformer Without Convolution or Region SupervisionWonjae Kim, Bokyung Son, Ildoo Kim. 5583-5594 [doi]
• Bias-Robust Bayesian Optimization via Dueling BanditsJohannes Kirschner, Andreas Krause 0001. 5595-5605 [doi]
• CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and PatientsDani Kiyasseh, Tingting Zhu, David A. Clifton. 5606-5615 [doi]
• Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and MoreJohannes Klicpera, Marten Lienen, Stephan Günnemann. 5616-5627 [doi]
• Representational aspects of depth and conditioning in normalizing flowsFrederic Koehler, Viraj Mehta, Andrej Risteski. 5628-5636 [doi]
• WILDS: A Benchmark of in-the-Wild Distribution ShiftsPang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton Earnshaw, Imran Haque, Sara M. Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang. 5637-5664 [doi]
• One-sided Frank-Wolfe algorithms for saddle problemsVladimir Kolmogorov, Thomas Pock. 5665-5675 [doi]
• A Lower Bound for the Sample Complexity of Inverse Reinforcement LearningAbi Komanduru, Jean Honorio. 5676-5685 [doi]
• Consensus Control for Decentralized Deep LearningLingjing Kong 0001, Tao Lin 0004, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich. 5686-5696 [doi]
• A Distribution-dependent Analysis of Meta LearningMikhail Konobeev, Ilja Kuzborskij, Csaba Szepesvári. 5697-5706 [doi]
• Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?Anna-Kathrin Kopetzki, Bertrand Charpentier, Daniel Zügner, Sandhya Giri, Stephan Günnemann. 5707-5718 [doi]
• Kernel Stein Discrepancy DescentAnna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin. 5719-5730 [doi]
• Boosting the Throughput and Accelerator Utilization of Specialized CNN Inference Beyond Increasing Batch SizeJack Kosaian, Amar Phanishayee, Matthai Philipose, Debadeepta Dey, Rashmi Vinayak. 5731-5741 [doi]
• NeRF-VAE: A Geometry Aware 3D Scene Generative ModelAdam R. Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokrá, Danilo Jimenez Rezende. 5742-5752 [doi]
• Active Testing: Sample-Efficient Model EvaluationJannik Kossen, Sebastian Farquhar, Yarin Gal, Tom Rainforth. 5753-5763 [doi]
• High Confidence Generalization for Reinforcement LearningJames Kostas, Yash Chandak, Scott M. Jordan, Georgios Theocharous, Philip S. Thomas. 5764-5773 [doi]
• Offline Reinforcement Learning with Fisher Divergence Critic RegularizationIlya Kostrikov, Rob Fergus, Jonathan Tompson, Ofir Nachum. 5774-5783 [doi]
• ADOM: Accelerated Decentralized Optimization Method for Time-Varying NetworksDmitry Kovalev, Egor Shulgin, Peter Richtárik, Alexander Rogozin, Alexander Gasnikov. 5784-5793 [doi]
• Revisiting Peng's Q(λ) for Modern Reinforcement LearningTadashi Kozuno, Yunhao Tang, Mark Rowland, Rémi Munos, Steven Kapturowski, Will Dabney, Michal Valko, David Abel. 5794-5804 [doi]
• Adapting to misspecification in contextual bandits with offline regression oraclesSanath Kumar Krishnamurthy, Vitor Hadad, Susan Athey. 5805-5814 [doi]
• Out-of-Distribution Generalization via Risk Extrapolation (REx)David Krueger, Ethan Caballero, Jörn-Henrik Jacobsen, Amy Zhang 0001, Jonathan Binas, Dinghuai Zhang, Rémi Le Priol, Aaron C. Courville. 5815-5826 [doi]
• Near-Optimal Confidence Sequences for Bounded Random VariablesArun K. Kuchibhotla, Qinqing Zheng. 5827-5837 [doi]
• Differentially Private Bayesian Inference for Generalized Linear ModelsTejas Kulkarni, Joonas Jälkö, Antti Koskela, Samuel Kaski, Antti Honkela. 5838-5849 [doi]
• Bayesian Structural Adaptation for Continual LearningAbhishek Kumar 0001, Sunabha Chatterjee, Piyush Rai. 5850-5860 [doi]
• Implicit rate-constrained optimization of non-decomposable objectivesAbhishek Kumar, Harikrishna Narasimhan, Andrew Cotter. 5861-5871 [doi]
• A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few SamplesChristian Kümmerle, Claudio Mayrink Verdun. 5872-5883 [doi]
• Meta-Thompson SamplingBranislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-Wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvári. 5884-5893 [doi]
• Targeted Data Acquisition for Evolving Negotiation AgentsMinae Kwon, Siddharth Karamcheti, Mariano-Florentino Cuellar, Dorsa Sadigh. 5894-5904 [doi]
• ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural NetworksJungmin Kwon, Jeongseop Kim, Hyunseo Park, In Kwon Choi. 5905-5914 [doi]
• On the price of explainability for some clustering problemsEduardo Sany Laber, Lucas Murtinho. 5915-5925 [doi]
• Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian DimensionalityJonathan Lacotte, Yifei Wang, Mert Pilanci. 5926-5936 [doi]
• Generalization Bounds in the Presence of Outliers: a Median-of-Means StudyPierre Laforgue, Guillaume Staerman, Stéphan Clémençon. 5937-5947 [doi]
• Model Fusion for Personalized LearningThanh Chi Lam, Trong Nghia Hoang, Bryan Kian Hsiang Low, Patrick Jaillet. 5948-5958 [doi]
• Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant MatrixMaximilian Lam, Gu-Yeon Wei, David Brooks 0001, Vijay Janapa Reddi, Michael Mitzenmacher. 5959-5968 [doi]
• Stochastic Multi-Armed Bandits with Unrestricted Delay DistributionsTal Lancewicki, Shahar Segal, Tomer Koren, Yishay Mansour. 5969-5978 [doi]
• Discovering symbolic policies with deep reinforcement learningMikel Landajuela Larma, Brenden K. Petersen, Sookyung Kim, Cláudio P. Santiago, Ruben Glatt, Nathan Mundhenk, Jacob F. Pettit, Daniel Faissol. 5979-5989 [doi]
• Graph Cuts Always Find a Global Optimum for Potts Models (With a Catch)Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan. 5990-5999 [doi]
• Efficient Message Passing for 0-1 ILPs with Binary Decision DiagramsJan-Hendrik Lange, Paul Swoboda. 6000-6010 [doi]
• CountSketches, Feature Hashing and the Median of ThreeKasper Green Larsen, Rasmus Pagh, Jakub Tetek. 6011-6020 [doi]
• MorphVAE: Generating Neural Morphologies from 3D-Walks using a Variational Autoencoder with Spherical Latent SpaceSophie Laturnus, Philipp Berens. 6021-6031 [doi]
• Improved Regret Bound and Experience Replay in Regularized Policy IterationNevena Lazic, Dong Yin, Yasin Abbasi-Yadkori, Csaba Szepesvári. 6032-6042 [doi]
• LAMDA: Label Matching Deep Domain AdaptationTrung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung 0001. 6043-6054 [doi]
• Gaussian Process-Based Real-Time Learning for Safety Critical ApplicationsArmin Lederer, Alejandro Jose Ordóñez Conejo, Korbinian Maier, Wenxin Xiao, Jonas Umlauft, Sandra Hirche. 6055-6064 [doi]
• Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer TransferSeungWon Lee, Sima Behpour, Eric Eaton. 6065-6075 [doi]
• Fair Selective Classification Via SufficiencyJoshua K. Lee, Yuheng Bu, Deepta Rajan, Prasanna Sattigeri, Rameswar Panda, Subhro Das, Gregory W. Wornell. 6076-6086 [doi]
• On-the-fly Rectification for Robust Large-Vocabulary Topic InferenceMoontae Lee, Sungjun Cho, Kun Dong, David Mimno, David Bindel. 6087-6097 [doi]
• Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot ClassificationDong-Hoon Lee, Sae-Young Chung. 6098-6108 [doi]
• Continual Learning in the Teacher-Student Setup: Impact of Task SimilaritySebastian Lee, Sebastian Goldt, Andrew M. Saxe. 6109-6119 [doi]
• OptiDICE: Offline Policy Optimization via Stationary Distribution Correction EstimationJongmin Lee 0004, Wonseok Jeon, Byung-Jun Lee 0001, Joelle Pineau, Kee-Eung Kim. 6120-6130 [doi]
• SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement LearningKimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel. 6131-6141 [doi]
• Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits SimultaneouslyChung-wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang 0002. 6142-6151 [doi]
• PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-trainingKimin Lee, Laura M. Smith, Pieter Abbeel. 6152-6163 [doi]
• Near-Optimal Linear Regression under Distribution ShiftQi Lei, Wei Hu, Jason Lee. 6164-6174 [doi]
• Stability and Generalization of Stochastic Gradient Methods for Minimax ProblemsYunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying. 6175-6186 [doi]
• Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting PotJoel Z. Leibo, Edgar A. Duéñez-Guzmán, Alexander Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, Thore Graepel. 6187-6199 [doi]
• Better Training using Weight-Constrained Stochastic DynamicsBenedict J. Leimkuhler, Tiffany J. Vlaar, Timothée Pouchon, Amos J. Storkey. 6200-6211 [doi]
• Globally-Robust Neural NetworksKlas Leino, Zifan Wang, Matt Fredrikson. 6212-6222 [doi]
• Learning to Price Against a Moving TargetRenato Paes Leme, Balasubramanian Sivan, Yifeng Teng, Pratik Worah. 6223-6232 [doi]
• SigGPDE: Scaling Sparse Gaussian Processes on Sequential DataMaud Lemercier, Cristopher Salvi, Thomas Cass, Edwin V. Bonilla, Theodoros Damoulas, Terry J. Lyons. 6233-6242 [doi]
• Strategic Classification Made PracticalSagi Levanon, Nir Rosenfeld. 6243-6253 [doi]
• 1 Certified RobustnessAlexander Levine 0001, Soheil Feizi. 6254-6264 [doi]
• BASE Layers: Simplifying Training of Large, Sparse ModelsMike Lewis, Shruti Bhosale, Tim Dettmers, Naman Goyal, Luke Zettlemoyer. 6265-6274 [doi]
• Run-Sort-ReRun: Escaping Batch Size Limitations in Sliced Wasserstein Generative ModelsJosé Lezama, Wei Chen, Qiang Qiu. 6275-6285 [doi]
• PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex OptimizationZhize Li, Hongyan Bao, Xiangliang Zhang 0001, Peter Richtárik. 6286-6295 [doi]
• Tightening the Dependence on Horizon in the Sample Complexity of Q-LearningGen Li 0005, Changxiao Cai, Yuxin Chen 0002, Yuantao Gu, Yuting Wei, Yuejie Chi. 6296-6306 [doi]
• Winograd Algorithm for AdderNetWenshuo Li, Hanting Chen, Mingqiang Huang, Xinghao Chen 0001, Chunjing Xu, Yunhe Wang 0001. 6307-6315 [doi]
• A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks CalibrationYuhang Li, Shikuang Deng, Xin Dong 0009, Ruihao Gong, Shi Gu. 6316-6325 [doi]
• Privacy-Preserving Feature Selection with Secure Mul