Table of Contents

• PAC-Bayesian Bounds on Rate-Efficient ClassifiersAlhabib Abbas, Yiannis Andreopoulos. 1-9 [doi]
• Sharp-MAML: Sharpness-Aware Model-Agnostic Meta LearningMomin Abbas, Quan Xiao, Lisha Chen, Pin-Yu Chen, Tianyi Chen. 10-32 [doi]
• An Initial Alignment between Neural Network and Target is Needed for Gradient Descent to LearnEmmanuel Abbe, Elisabetta Cornacchia, Jan Hazla, Christopher Marquis. 33-52 [doi]
• Active Sampling for Min-Max FairnessJacob D. Abernethy, Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern, Chris Russell 0001, Jie Zhang. 53-65 [doi]
• Meaningfully debugging model mistakes using conceptual counterfactual explanationsAbubakar Abid, Mert Yüksekgönül, James Zou 0001. 66-88 [doi]
• Batched Dueling BanditsArpit Agarwal, Rohan Ghuge, Viswanath Nagarajan. 89-110 [doi]
• Hierarchical Shrinkage: Improving the accuracy and interpretability of tree-based modelsAbhineet Agarwal, Yan Shuo Tan, Omer Ronen, Chandan Singh, Bin Yu 0001. 111-135 [doi]
• Deep equilibrium networks are sensitive to initialization statisticsAtish Agarwala, Samuel S. Schoenholz. 136-160 [doi]
• Learning of Cluster-based Feature Importance for Electronic Health Record Time-seriesHenrique Aguiar, Mauro D. Santos, Peter J. Watkinson, Tingting Zhu 0001. 161-179 [doi]
• On the Convergence of the Shapley Value in Parametric Bayesian Learning GamesLucas Agussurja, Xinyi Xu, Bryan Kian Hsiang Low. 180-196 [doi]
• Individual Preference Stability for ClusteringSaba Ahmadi, Pranjal Awasthi, Samir Khuller, Matthäus Kleindessner, Jamie Morgenstern, Pattara Sukprasert, Ali Vakilian. 197-246 [doi]
• Understanding the unstable convergence of gradient descentKwangjun Ahn, Jingzhao Zhang, Suvrit Sra. 247-257 [doi]
• Minimum Cost Intervention Design for Causal Effect IdentificationSina Akbari, Jalal Etesami, Negar Kiyavash. 258-289 [doi]
• How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative ModelsAhmed Alaa, Boris van Breugel, Evgeny S. Saveliev, Mihaela van der Schaar. 290-306 [doi]
• A Natural Actor-Critic Framework for Zero-Sum Markov GamesAhmet Alacaoglu, Luca Viano, Niao He, Volkan Cevher. 307-366 [doi]
• Deploying Convolutional Networks on Untrusted Platforms Using 2D Holographic Reduced RepresentationsMohammad Mahmudul Alam, Edward Raff, Tim Oates, James Holt. 367-393 [doi]
• Optimistic Linear Support and Successor Features as a Basis for Optimal Policy TransferLucas Nunes Alegre, Ana L. C. Bazzan, Bruno C. da Silva 0001. 394-413 [doi]
• Structured Stochastic Gradient MCMCAntonios Alexos, Alex J. Boyd, Stephan Mandt. 414-434 [doi]
• XAI for Transformers: Better Explanations through Conservative PropagationAmeen Ali, Thomas Schnake, Oliver Eberle, Grégoire Montavon, Klaus-Robert Müller, Lior Wolf. 435-451 [doi]
• RUMs from Head-to-Head ContestsMatteo Almanza, Flavio Chierichetti, Ravi Kumar 0001, Alessandro Panconesi, Andrew Tomkins. 452-467 [doi]
• Neuro-Symbolic Language Modeling with Automaton-augmented RetrievalUri Alon 0002, Frank F. Xu, Junxian He, Sudipta Sengupta, Dan Roth, Graham Neubig. 468-485 [doi]
• Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance GuaranteesVerónica Álvarez, Santiago Mazuelas, José Antonio Lozano. 486-499 [doi]
• Scalable First-Order Bayesian Optimization via Structured Automatic DifferentiationSebastian E. Ament, Carla P. Gomes. 500-516 [doi]
• Public Data-Assisted Mirror Descent for Private Model TrainingEhsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song 0001, Thomas Steinke 0002, Vinith M. Suriyakumar, Om Thakkar 0001, Abhradeep Thakurta. 517-535 [doi]
• On Last-Iterate Convergence Beyond Zero-Sum GamesIoannis Anagnostides, Ioannis Panageas, Gabriele Farina, Tuomas Sandholm. 536-581 [doi]
• Online Algorithms with Multiple PredictionsKeerti Anand, Rong Ge 0001, Amit Kumar, Debmalya Panigrahi. 582-598 [doi]
• Learning to Hash Robustly, GuaranteedAlexandr Andoni, Daniel Beaglehole. 599-618 [doi]
• Set Based Stochastic SubsamplingBruno Andreis, Seanie Lee, Tuan A. Nguyen, Juho Lee 0001, Eunho Yang, Sung Ju Hwang. 619-638 [doi]
• Towards Understanding Sharpness-Aware MinimizationMaksym Andriushchenko, Nicolas Flammarion. 639-668 [doi]
• Fair and Fast k-Center Clustering for Data SummarizationHaris Angelidakis, Adam Kurpisz, Leon Sering, Rico Zenklusen. 669-702 [doi]
• Interactive Correlation Clustering with Existential Cluster ConstraintsRico Angell, Nicholas Monath, Nishant Yadav, Andrew McCallum. 703-716 [doi]
• Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in ImagingAnastasios N. Angelopoulos, Amit Pal Singh Kohli, Stephen Bates, Michael I. Jordan, Jitendra Malik, Thayer Alshaabi, Srigokul Upadhyayula, Yaniv Romano. 717-730 [doi]
• AdaGrad Avoids Saddle PointsKimon Antonakopoulos, Panayotis Mertikopoulos, Georgios Piliouras, Xiao Wang 0036. 731-771 [doi]
• UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate GuaranteesKimon Antonakopoulos, Dong Quan Vu, Volkan Cevher, Kfir Y. Levy, Panayotis Mertikopoulos. 772-795 [doi]
• Adapting the Linearised Laplace Model Evidence for Modern Deep LearningJavier Antorán, David Janz, James Urquhart Allingham, Erik A. Daxberger, Riccardo Barbano, Eric T. Nalisnick, José Miguel Hernández-Lobato. 796-821 [doi]
• EAT-C: Environment-Adversarial sub-Task Curriculum for Efficient Reinforcement LearningShuang Ao, Tianyi Zhou, Jing Jiang 0002, Guodong Long, Xuan Song, Chengqi Zhang. 822-843 [doi]
• Online Balanced Experimental DesignDavid Arbour, Drew Dimmery, Tung Mai, Anup B. Rao. 844-864 [doi]
• VariGrow: Variational Architecture Growing for Task-Agnostic Continual Learning based on Bayesian NoveltyRandy Ardywibowo, Zepeng Huo, Zhangyang Wang, Bobak J. Mortazavi, Shuai Huang, Xiaoning Qian. 865-877 [doi]
• Thresholded Lasso BanditKaito Ariu, Kenshi Abe, Alexandre Proutière. 878-928 [doi]
• Gradient Based ClusteringAleksandar Armacki, Dragana Bajovic, Dusan Jakovetic, Soummya Kar. 929-947 [doi]
• Understanding Gradient Descent on the Edge of Stability in Deep LearningSanjeev Arora, Zhiyuan Li 0005, Abhishek Panigrahi. 948-1024 [doi]
• Private optimization in the interpolation regime: faster rates and hardness resultsHilal Asi, Karan N. Chadha, Gary Cheng 0004, John Duchi. 1025-1045 [doi]
• Optimal Algorithms for Mean Estimation under Local Differential PrivacyHilal Asi, Vitaly Feldman, Kunal Talwar. 1046-1056 [doi]
• Asymptotically-Optimal Gaussian Bandits with Side ObservationsAlexia Atsidakou, Orestis Papadigenopoulos, Constantine Caramanis, Sujay Sanghavi, Sanjay Shakkottai. 1057-1077 [doi]
• Congested Bandits: Optimal Routing via Short-term ResetsPranjal Awasthi, Kush Bhatia, Sreenivas Gollapudi, Kostas Kollias. 1078-1100 [doi]
• Do More Negative Samples Necessarily Hurt In Contrastive Learning?Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath. 1101-1116 [doi]
• H-Consistency Bounds for Surrogate Loss MinimizersPranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong 0002. 1117-1174 [doi]
• Iterative Hard Thresholding with Adaptive Regularization: Sparser Solutions Without Sacrificing RuntimeKyriakos Axiotis, Maxim Sviridenko. 1175-1197 [doi]
• Proving Theorems using Incremental Learning and Hindsight Experience ReplayEser Aygün, Ankit Anand, Laurent Orseau, Xavier Glorot, Stephen M. McAleer, Vlad Firoiu, Lei M. Zhang, Doina Precup, Shibl Mourad. 1198-1210 [doi]
• Near-optimal rate of consistency for linear models with missing valuesAlexis Ayme, Claire Boyer, Aymeric Dieuleveut, Erwan Scornet. 1211-1243 [doi]
• How Tempering Fixes Data Augmentation in Bayesian Neural NetworksGregor Bachmann, Lorenzo Noci, Thomas Hofmann. 1244-1260 [doi]
• ASAP.SGD: Instance-based Adaptiveness to Staleness in Asynchronous SGDKarl Bäckström, Marina Papatriantafilou, Philippas Tsigas. 1261-1276 [doi]
• From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative ModelHeeSun Bae, SeungJae Shin, Byeonghu Na, JoonHo Jang, Kyungwoo Song, Il-Chul Moon. 1277-1297 [doi]
• data2vec: A General Framework for Self-supervised Learning in Speech, Vision and LanguageAlexei Baevski, Wei-Ning Hsu, Qiantong Xu, Arun Babu, Jiatao Gu, Michael Auli. 1298-1312 [doi]
• End-to-End Balancing for Causal Continuous Treatment-Effect EstimationMohammad Taha Bahadori, Eric Tchetgen Tchetgen, David Heckerman. 1313-1326 [doi]
• A Hierarchical Transitive-Aligned Graph Kernel for Un-attributed GraphsLu Bai, Lixin Cui, Edwin R. Hancock. 1327-1336 [doi]
• Near-Optimal Learning of Extensive-Form Games with Imperfect InformationYu Bai, Chi Jin, Song Mei, Tiancheng Yu. 1337-1382 [doi]
• Gaussian Mixture Variational Autoencoder with Contrastive Learning for Multi-Label ClassificationJunwen Bai, Shufeng Kong, Carla P. Gomes. 1383-1398 [doi]
• 3T: Alignment-Aware Acoustic and Text Pretraining for Speech Synthesis and EditingHe Bai, Renjie Zheng, Junkun Chen, Mingbo Ma, Xintong Li, Liang Huang 0001. 1399-1411 [doi]
• Stability Based Generalization Bounds for Exponential Family Langevin DynamicsArindam Banerjee 0001, Tiancong Chen, Xinyan Li, Yingxue Zhou. 1412-1449 [doi]
• Certified Neural Network Watermarks with Randomized SmoothingArpit Bansal, Ping-Yeh Chiang, Michael J. Curry, Rajiv Jain, Curtis Wigington, Varun Manjunatha, John P. Dickerson, Tom Goldstein. 1450-1465 [doi]
• Data Scaling Laws in NMT: The Effect of Noise and ArchitectureYamini Bansal, Behrooz Ghorbani, Ankush Garg, Biao Zhang, Colin Cherry, Behnam Neyshabur, Orhan Firat. 1466-1482 [doi]
• Learning Stable Classifiers by Transferring Unstable FeaturesYujia Bao, Shiyu Chang, Regina Barzilay. 1483-1507 [doi]
• Fast Composite Optimization and Statistical Recovery in Federated LearningYajie Bao, Michael Crawshaw, Shan Luo, Mingrui Liu. 1508-1536 [doi]
• Generative Modeling for Multi-task Visual LearningZhipeng Bao, Martial Hebert, Yu-Xiong Wang. 1537-1554 [doi]
• Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic ModelsFan Bao, Chongxuan Li, Jiacheng Sun, Jun Zhu, Bo Zhang. 1555-1584 [doi]
• On the Surrogate Gap between Contrastive and Supervised LossesHan Bao 0002, Yoshihiro Nagano, Kento Nozawa. 1585-1606 [doi]
• Representation Topology Divergence: A Method for Comparing Neural Network RepresentationsSerguei Barannikov, Ilya Trofimov, Nikita Balabin, Evgeny Burnaev. 1607-1626 [doi]
• Sparse Mixed Linear Regression with Guarantees: Taming an Intractable Problem with Invex RelaxationAdarsh Barik, Jean Honorio. 1627-1646 [doi]
• Neural Fisher Discriminant Analysis: Optimal Neural Network Embeddings in Polynomial TimeBurak Bartan, Mert Pilanci. 1647-1663 [doi]
• Fictitious Play and Best-Response Dynamics in Identical Interest and Zero-Sum Stochastic GamesLucas Baudin, Rida Laraki. 1664-1690 [doi]
• Information Discrepancy in Strategic LearningYahav Bechavod, Chara Podimata, Zhiwei Steven Wu, Juba Ziani. 1691-1715 [doi]
• On the Hidden Biases of Policy Mirror Ascent in Continuous Action SpacesAmrit Singh Bedi, Souradip Chakraborty, Anjaly Parayil, Brian M. Sadler, Pratap Tokekar, Alec Koppel. 1716-1731 [doi]
• Imitation Learning by Estimating Expertise of DemonstratorsMark Beliaev, Andy Shih, Stefano Ermon, Dorsa Sadigh, Ramtin Pedarsani. 1732-1748 [doi]
• Matching Normalizing Flows and Probability Paths on ManifoldsHeli Ben Hamu, Samuel Cohen, Joey Bose, Brandon Amos, Maximilian Nickel, Aditya Grover, Ricky T. Q. Chen, Yaron Lipman. 1749-1763 [doi]
• Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity ModelsViktor Bengs, Aadirupa Saha, Eyke Hüllermeier. 1764-1786 [doi]
• Neural Inverse KinematicRaphael Bensadoun, Shir Gur, Nitsan Blau, Lior Wolf. 1787-1797 [doi]
• Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian ProcessesGregory W. Benton, Wesley J. Maddox, Andrew Gordon Wilson. 1798-1816 [doi]
• Gradient Descent on Neurons and its Link to Approximate Second-order OptimizationFrederik Benzing. 1817-1853 [doi]
• Safe Learning in Tree-Form Sequential Decision Making: Handling Hard and Soft ConstraintsMartino Bernasconi, Federico Cacciamani, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti 0001, Francesco Trovò. 1854-1873 [doi]
• Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma ClassificationPeter J. Bevan, Amir Atapour Abarghouei. 1874-1892 [doi]
• Approximate Bayesian Computation with Domain Expert in the LoopAyush Bharti, Louis Filstroff, Samuel Kaski. 1893-1905 [doi]
• Minimax M-estimation under Adversarial ContaminationSujay Bhatt, Guanhua Fang, Ping Li 0001, Gennady Samorodnitsky. 1906-1924 [doi]
• Nearly Optimal Catoni's M-estimator for Infinite VarianceSujay Bhatt, Guanhua Fang, Ping Li 0001, Gennady Samorodnitsky. 1925-1944 [doi]
• Personalization Improves Privacy-Accuracy Tradeoffs in Federated LearningAlberto Bietti, Chen-Yu Wei, Miroslav Dudík, John Langford 0001, Zhiwei Steven Wu. 1945-1962 [doi]
• Non-Vacuous Generalisation Bounds for Shallow Neural NetworksFelix Biggs, Benjamin Guedj. 1963-1981 [doi]
• Structure-preserving GANsJeremiah Birrell, Markos A. Katsoulakis, Luc Rey-Bellet, Wei Zhu. 1982-2020 [doi]
• Scalable Spike-and-SlabNiloy Biswas, Lester Mackey, Xiao-Li Meng. 2021-2040 [doi]
• Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core QuantitiesJulian Bitterwolf, Alexander Meinke, Maximilian Augustin, Matthias Hein 0001. 2041-2074 [doi]
• A query-optimal algorithm for finding counterfactualsGuy Blanc, Caleb Koch, Jane Lange, Li-Yang Tan. 2075-2090 [doi]
• Popular decision tree algorithms are provably noise tolerantGuy Blanc, Jane Lange, Ali Malik, Li-Yang Tan. 2091-2106 [doi]
• Optimizing Sequential Experimental Design with Deep Reinforcement LearningTom Blau, Edwin V. Bonilla, Iadine Chades, Amir Dezfouli. 2107-2128 [doi]
• Lagrangian Method for Q-Function Learning (with Applications to Machine Translation)Bojun Huang. 2129-2159 [doi]
• Generalized Results for the Existence and Consistency of the MLE in the Bradley-Terry-Luce ModelHeejong Bong, Alessandro Rinaldo. 2160-2177 [doi]
• How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment PerspectiveAkhilan Boopathy, Ila Fiete. 2178-2205 [doi]
• Improving Language Models by Retrieving from Trillions of TokensSebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George van den Driessche 0002, Jean-Baptiste Lespiau, Bogdan Damoc, Aidan Clark, Diego de Las Casas, Aurelia Guy, Jacob Menick, Roman Ring, Tom Hennigan, Saffron Huang, Loren Maggiore, Chris Jones, Albin Cassirer, Andy Brock, Michela Paganini, Geoffrey Irving, Oriol Vinyals, Simon Osindero, Karen Simonyan, Jack W. Rae, Erich Elsen, Laurent Sifre. 2206-2240 [doi]
• Lie Point Symmetry Data Augmentation for Neural PDE SolversJohannes Brandstetter, Max Welling, Daniel E. Worrall. 2241-2256 [doi]
• An iterative clustering algorithm for the Contextual Stochastic Block Model with optimality guaranteesGuillaume Braun, Hemant Tyagi, Christophe Biernacki. 2257-2291 [doi]
• Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical SystemsManuel Brenner, Florian Hess, Jonas M. Mikhaeil, Leonard F. Bereska, Zahra Monfared, Po-Chen Kuo, Daniel Durstewitz. 2292-2320 [doi]
• Learning to Predict Graphs with Fused Gromov-Wasserstein BarycentersLuc Brogat-Motte, Rémi Flamary, Céline Brouard, Juho Rousu, Florence d'Alché-Buc. 2321-2335 [doi]
• Efficient Learning of CNNs using Patch Based FeaturesAlon Brutzkus, Amir Globerson, Eran Malach, Alon Regev Netser, Shai Shalev-Shwartz. 2336-2356 [doi]
• Causal structure-based root cause analysis of outliersKailash Budhathoki, Lenon Minorics, Patrick Blöbaum, Dominik Janzing. 2357-2369 [doi]
• IGLUE: A Benchmark for Transfer Learning across Modalities, Tasks, and LanguagesEmanuele Bugliarello, Fangyu Liu 0001, Jonas Pfeiffer, Siva Reddy, Desmond Elliott, Edoardo Maria Ponti, Ivan Vulic. 2370-2392 [doi]
• Interactive Inverse Reinforcement Learning for Cooperative GamesThomas Kleine Büning, Anne-Marie George, Christos Dimitrakakis. 2393-2413 [doi]
• Convolutional and Residual Networks Provably Contain Lottery TicketsRebekka Burkholz. 2414-2433 [doi]
• Near-Optimal Algorithms for Autonomous Exploration and Multi-Goal Stochastic Shortest PathHaoyuan Cai, Tengyu Ma 0001, Simon S. Du. 2434-2456 [doi]
• Convergence of Invariant Graph NetworksChen Cai, Yusu Wang. 2457-2484 [doi]
• Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample EfficiencyQi Cai, Zhuoran Yang, Zhaoran Wang. 2485-2522 [doi]
• Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple TimesDaniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco. 2523-2541 [doi]
• Adaptive Gaussian Process Change Point DetectionEdoardo Caldarelli, Philippe Wenk, Stefan Bauer, Andreas Krause 0001. 2542-2571 [doi]
• Measuring dissimilarity with diffeomorphism invarianceThéophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi. 2572-2596 [doi]
• A Model-Agnostic Randomized Learning Framework based on Random Hypothesis Subspace SamplingYiting Cao, Chao Lan. 2597-2608 [doi]
• Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical ApplicationsAlexandre Capone, Armin Lederer, Sandra Hirche. 2609-2624 [doi]
• Burst-Dependent Plasticity and Dendritic Amplification Support Target-Based Learning and Hierarchical Imitation LearningCristiano Capone, Cosimo Lupo, Paolo Muratore, Pier Stanislao Paolucci. 2625-2637 [doi]
• A Marriage between Adversarial Team Games and 2-player Games: Enabling Abstractions, No-regret Learning, and Subgame SolvingLuca Carminati, Federico Cacciamani, Marco Ciccone, Nicola Gatti 0001. 2638-2657 [doi]
• RECAPP: Crafting a More Efficient Catalyst for Convex OptimizationYair Carmon, Arun Jambulapati, Yujia Jin, Aaron Sidford. 2658-2685 [doi]
• Estimating and Penalizing Induced Preference Shifts in Recommender SystemsMicah D. Carroll, Anca D. Dragan, Stuart Russell 0001, Dylan Hadfield-Menell. 2686-2708 [doi]
• YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for EveryoneEdresson Casanova, Julian Weber, Christopher Dane Shulby, Arnaldo Cândido Júnior, Eren Gölge, Moacir A. Ponti. 2709-2720 [doi]
• The Infinite Contextual Graph Markov ModelDaniele Castellana, Federico Errica, Davide Bacciu, Alessio Micheli. 2721-2737 [doi]
• Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned DataTimothy J. Castiglia, Anirban Das, Shiqiang Wang 0001, Stacy Patterson. 2738-2766 [doi]
• Online Learning with Knapsacks: the Best of Both WorldsMatteo Castiglioni, Andrea Celli, Christian Kroer. 2767-2783 [doi]
• Stabilizing Off-Policy Deep Reinforcement Learning from PixelsEdoardo Cetin, Philip J. Ball, Stephen J. Roberts, Oya Çeliktutan. 2784-2810 [doi]
• Accelerated, Optimal and Parallel: Some results on model-based stochastic optimizationKaran N. Chadha, Gary Cheng 0004, John C. Duchi. 2811-2827 [doi]
• Robust Imitation Learning against Variations in Environment DynamicsJongseong Chae, Seungyul Han, Whiyoung Jung, Myungsik Cho, Sungho Choi, Youngchul Sung. 2828-2852 [doi]
• Fairness with Adaptive WeightsJunyi Chai, Xiaoqian Wang. 2853-2866 [doi]
• UNIREX: A Unified Learning Framework for Language Model Rationale ExtractionAaron Chan, Maziar Sanjabi, Lambert Mathias, Liang Tan 0005, Shaoliang Nie, Xiaochang Peng, Xiang Ren, Hamed Firooz. 2867-2889 [doi]
• Revisiting Label Smoothing and Knowledge Distillation Compatibility: What was Missing?Keshigeyan Chandrasegaran, Ngoc-Trung Tran, Yunqing Zhao, Ngai-Man Cheung. 2890-2916 [doi]
• Style Equalization: Unsupervised Learning of Controllable Generative Sequence ModelsJen-Hao Rick Chang, Ashish Shrivastava, Hema Koppula, Xiaoshuai Zhang, Oncel Tuzel. 2917-2937 [doi]
• Learning Bellman Complete Representations for Offline Policy EvaluationJonathan Chang, Kaiwen Wang, Nathan Kallus, Wen Sun. 2938-2971 [doi]
• Sample Efficient Learning of Predictors that Complement HumansMohammad-Amin Charusaie, Hussein Mozannar, David A. Sontag, Samira Samadi. 2972-3005 [doi]
• Nyström Kernel Mean EmbeddingsAntoine Chatalic, Nicolas Schreuder, Lorenzo Rosasco, Alessandro Rudi. 3006-3024 [doi]
• Coarsening the Granularity: Towards Structurally Sparse Lottery TicketsTianlong Chen, Xuxi Chen, Xiaolong Ma, Yanzhi Wang, Zhangyang Wang. 3025-3039 [doi]
• Learning Domain Adaptive Object Detection with Probabilistic TeacherMeilin Chen, Weijie Chen, Shicai Yang, Jie Song, Xinchao Wang, Lei Zhang, Yunfeng Yan, Donglian Qi, Yueting Zhuang, Di Xie, Shiliang Pu. 3040-3055 [doi]
• The Fundamental Price of Secure Aggregation in Differentially Private Federated LearningWei-Ning Chen, Christopher A. Choquette-Choo, Peter Kairouz, Ananda Theertha Suresh. 3056-3089 [doi]
• Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive LearningMayee F. Chen, Daniel Y. Fu, Avanika Narayan, Michael Zhang, Zhao Song 0002, Kayvon Fatahalian, Christopher Ré. 3090-3122 [doi]
• Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and RiskTianrui Chen, Aditya Gangrade, Venkatesh Saligrama. 3123-3148 [doi]
• On the Sample Complexity of Learning Infinite-horizon Discounted Linear Kernel MDPsYuanzhou Chen, Jiafan He, Quanquan Gu. 3149-3183 [doi]
• Streaming Algorithms for Support-Aware HistogramsJustin Y. Chen, Piotr Indyk, Tal Wagner. 3184-3203 [doi]
• Improved No-Regret Algorithms for Stochastic Shortest Path with Linear MDPLiyu Chen, Rahul Jain 0002, Haipeng Luo. 3204-3245 [doi]
• Learning Infinite-horizon Average-reward Markov Decision Process with ConstraintsLiyu Chen, Rahul Jain 0002, Haipeng Luo. 3246-3270 [doi]
• Active Multi-Task Representation LearningYifang Chen, Kevin G. Jamieson, Simon S. Du. 3271-3298 [doi]
• On Collective Robustness of Bagging Against Data PoisoningRuoxin Chen, Zenan Li, Jie Li 0002, Junchi Yan, Chentao Wu. 3299-3319 [doi]
• Online Active RegressionCheng Chen, Yi Li 0002, Yiming Sun. 3320-3335 [doi]
• Selling Data To a Machine Learner: Pricing via Costly SignalingJunjie Chen, Minming Li, Haifeng Xu. 3336-3359 [doi]
• ME-GAN: Learning Panoptic Electrocardio Representations for Multi-view ECG Synthesis Conditioned on Heart DiseasesJintai Chen, Kuanlun Liao, Kun Wei, Haochao Ying, Danny Z. Chen, Jian Wu 0001. 3360-3370 [doi]
• Weisfeiler-Lehman Meets Gromov-WassersteinSamantha Chen, Sunhyuk Lim, Facundo Mémoli, Zhengchao Wan, Yusu Wang. 3371-3416 [doi]
• On Non-local Convergence Analysis of Deep Linear NetworksKun Chen, Dachao Lin, Zhihua Zhang. 3417-3443 [doi]
• Flow-based Recurrent Belief State Learning for POMDPsXiaoyu Chen, Yao Mark Mu, Ping Luo, Shengbo Li, Jianyu Chen. 3444-3468 [doi]
• Structure-Aware Transformer for Graph Representation LearningDexiong Chen, Leslie O'Bray, Karsten M. Borgwardt. 3469-3489 [doi]
• The Poisson Binomial Mechanism for Unbiased Federated Learning with Secure AggregationWei-Ning Chen, Ayfer Özgür, Peter Kairouz. 3490-3506 [doi]
• Learning Mixtures of Linear Dynamical SystemsYanxi Chen, H. Vincent Poor. 3507-3557 [doi]
• On Well-posedness and Minimax Optimal Rates of Nonparametric Q-function Estimation in Off-policy EvaluationXiaohong Chen, Zhengling Qi. 3558-3582 [doi]
• Faster Fundamental Graph Algorithms via Learned PredictionsJustin Y. Chen, Sandeep Silwal, Ali Vakilian, Fred Zhang. 3583-3602 [doi]
• Improve Single-Point Zeroth-Order Optimization Using High-Pass and Low-Pass FiltersXin Chen, Yujie Tang 0002, Na Li 0002. 3603-3620 [doi]
• Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly DetectionWenchao Chen, Long Tian, Bo Chen, Liang Dai, Zhibin Duan, Mingyuan Zhou. 3621-3633 [doi]
• Auxiliary Learning with Joint Task and Data SchedulingHong Chen, Xin Wang, Chaoyu Guan, Yue Liu, Wenwu Zhu 0001. 3634-3647 [doi]
• Optimization-Induced Graph Implicit Nonlinear DiffusionQi Chen, Yifei Wang, Yisen Wang 0001, Jiansheng Yang, Zhouchen Lin. 3648-3661 [doi]
• Robust Meta-learning with Sampling Noise and Label Noise via Eigen-ReptileDong Chen, Lingfei Wu, Siliang Tang, Xiao Yun, Bo Long, Yueting Zhuang. 3662-3678 [doi]
• Adaptive Model Design for Markov Decision ProcessSiyu Chen, Donglin Yang, Jiayang Li, Senmiao Wang, Zhuoran Yang, Zhaoran Wang. 3679-3700 [doi]
• State Transition of Dendritic Spines Improves Learning of Sparse Spiking Neural NetworksYanqi Chen, Zhaofei Yu, Wei Fang, Zhengyu Ma, Tiejun Huang 0001, Yonghong Tian 0001. 3701-3715 [doi]
• Efficient Online ML API Selection for Multi-Label Classification TasksLingjiao Chen, Matei Zaharia, James Zou 0001. 3716-3746 [doi]
• Data-Efficient Double-Win Lottery Tickets from Robust Pre-trainingTianlong Chen, Zhenyu Zhang, Sijia Liu 0001, Yang Zhang, Shiyu Chang, Zhangyang Wang. 3747-3759 [doi]
• Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable RobustnessTianlong Chen, Huan Zhang, Zhenyu Zhang, Shiyu Chang, Sijia Liu 0001, Pin-Yu Chen, Zhangyang Wang. 3760-3772 [doi]
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• Task-aware Privacy Preservation for Multi-dimensional DataJiangnan Cheng, Ao Tang, Sandeep Chinchali. 3835-3851 [doi]
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• Quantum-Inspired Algorithms from Randomized Numerical Linear AlgebraNadiia Chepurko, Kenneth L. Clarkson, Lior Horesh, Honghao Lin, David P. Woodruff. 3879-3900 [doi]
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• Shuffle Private Linear Contextual BanditsSayak Ray Chowdhury, Xingyu Zhou 0001. 3984-4009 [doi]
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• Context-Aware Drift DetectionOliver Cobb, Arnaud Van Looveren. 4087-4111 [doi]
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• Understanding Robust Generalization in Learning Regular LanguagesSoham Dan, Osbert Bastani, Dan Roth. 4630-4643 [doi]
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• Monarch: Expressive Structured Matrices for Efficient and Accurate TrainingTri Dao, Beidi Chen, Nimit Sharad Sohoni, Arjun D. Desai, Michael Poli, Jessica Grogan, Alexander Liu, Aniruddh Rao, Atri Rudra, Christopher Ré. 4690-4721 [doi]
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• Learning General Halfspaces with Adversarial Label Noise via Online Gradient DescentIlias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis. 5118-5141 [doi]
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• Understanding Doubly Stochastic ClusteringTianjiao Ding, Derek Lim, René Vidal, Benjamin D. Haeffele. 5153-5165 [doi]
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• Generalization and Robustness Implications in Object-Centric LearningAndrea Dittadi, Samuele S. Papa, Michele De Vita, Bernhard Schölkopf, Ole Winther, Francesco Locatello. 5221-5285 [doi]
• Fair Generalized Linear Models with a Convex PenaltyHyungrok Do, Preston Putzel, Axel S. Martin, Padhraic Smyth, Judy Zhong. 5286-5308 [doi]
• Bayesian Learning with Information Gain Provably Bounds Risk for a Robust Adversarial DefenseBao Gia Doan, Ehsan Abbasnejad, Javen Qinfeng Shi, Damith Ranashinghe. 5309-5323 [doi]
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• Finding the Task-Optimal Low-Bit Sub-Distribution in Deep Neural NetworksRunpei Dong, Zhanhong Tan, Mengdi Wu, Linfeng Zhang, Kaisheng Ma. 5343-5359 [doi]
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• Adapting to Mixing Time in Stochastic Optimization with Markovian DataRon Dorfman, Kfir Yehuda Levy. 5429-5446 [doi]
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• Branching Reinforcement LearningYihan Du, Wei Chen 0013. 5494-5530 [doi]
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• GLaM: Efficient Scaling of Language Models with Mixture-of-ExpertsNan Du, Yanping Huang, Andrew M. Dai, Simon Tong, Dmitry Lepikhin, Yuanzhong Xu, Maxim Krikun, Yanqi Zhou, Adams Wei Yu, Orhan Firat, Barret Zoph, Liam Fedus, Maarten P. Bosma, Zongwei Zhou, Tao Wang, Yu Emma Wang, Kellie Webster, Marie Pellat, Kevin Robinson, Kathleen S. Meier-Hellstern, Toju Duke, Lucas Dixon, Kun Zhang, Quoc V. Le, Yonghui Wu, Zhifeng Chen, Claire Cui. 5547-5569 [doi]
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• SE(3) Equivariant Graph Neural Networks with Complete Local FramesWeitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng 0001, Bin Shao, Tie-Yan Liu. 5583-5608 [doi]
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• Partial Label Learning via Label Influence FunctionXiuwen Gong, Dong Yuan, Wei Bao. 7665-7678 [doi]
• Secure Distributed Training at ScaleEduard Gorbunov, Alexander Borzunov, Michael Diskin, Max Ryabinin. 7679-7739 [doi]
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• Adapting k-means Algorithms for OutliersChristoph Grunau, Václav Rozhon. 7845-7886 [doi]
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• Learning Pseudometric-based Action Representations for Offline Reinforcement LearningPengjie Gu, Mengchen Zhao, Chen Chen, Dong Li, Jianye Hao, Bo An. 7902-7918 [doi]
• NeuroFluid: Fluid Dynamics Grounding with Particle-Driven Neural Radiance FieldsShanyan Guan, Huayu Deng, Yunbo Wang, Xiaokang Yang. 7919-7929 [doi]
• Fast-Rate PAC-Bayesian Generalization Bounds for Meta-LearningJiechao Guan, Zhiwu Lu 0001. 7930-7948 [doi]
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• Provably Efficient Offline Reinforcement Learning for Partially Observable Markov Decision ProcessesHongyi Guo, Qi Cai, Yufeng Zhang, Zhuoran Yang, Zhaoran Wang. 8016-8038 [doi]
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• p geometry with Applications in High Dimensional Online Decision MakingYuxuan Han, Zhicong Liang, Zhipeng Liang, Yang Wang, Yuan Yao, Jiheng Zhang. 8249-8279 [doi]
• Off-Policy Reinforcement Learning with Delayed RewardsBeining Han, Zhizhou Ren, Zuofan Wu, Yuan Zhou 0007, Jian Peng 0001. 8280-8303 [doi]
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• Temporal Difference Learning for Model Predictive ControlNicklas A. Hansen, Hao Su, Xiaolong Wang. 8387-8406 [doi]
• Bisimulation Makes Analogies in Goal-Conditioned Reinforcement LearningPhilippe Hansen-Estruch, Amy Zhang 0001, Ashvin Nair, Patrick Yin, Sergey Levine. 8407-8426 [doi]
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• Implicit Regularization with Polynomial Growth in Deep Tensor FactorizationKais Hariz, Hachem Kadri, Stéphane Ayache, Maher Moakher, Thierry Artières. 8484-8501 [doi]
• Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic ResponsesKeegan Harris, Dung Daniel T. Ngo, Logan Stapleton, Hoda Heidari, Steven Wu 0001. 8502-8522 [doi]
• C*-algebra Net: A New Approach Generalizing Neural Network Parameters to C*-algebraYuka Hashimoto, Zhao Wang, Tomoko Matsui. 8523-8534 [doi]
• General-purpose, long-context autoregressive modeling with Perceiver ARCurtis Hawthorne, Andrew Jaegle, Catalina Cangea, Sebastian Borgeaud, Charlie Nash, Mateusz Malinowski, Sander Dieleman, Oriol Vinyals, Matthew M. Botvinick, Ian Simon, Hannah Sheahan, Neil Zeghidour, Jean-Baptiste Alayrac, João Carreira, Jesse H. Engel. 8535-8558 [doi]
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• GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural NetworksYixuan He, Quan Gan, David Wipf, Gesine D. Reinert, Junchi Yan, Mihai Cucuringu. 8581-8612 [doi]
• Exploring the Gap between Collapsed & Whitened Features in Self-Supervised LearningBobby He, Mete Ozay. 8613-8634 [doi]
• Sparse Double Descent: Where Network Pruning Aggravates OverfittingZheng He, Zeke Xie, Quanzhi Zhu, Zengchang Qin. 8635-8659 [doi]
• A Reduction from Linear Contextual Bandit Lower Bounds to Estimation Lower BoundsJiahao He, Jiheng Zhang, Rachel Q. Zhang. 8660-8677 [doi]
• HyperPrompt: Prompt-based Task-Conditioning of TransformersYun He, Huaixiu Steven Zheng, Yi Tay, Jai Prakash Gupta, Yu Du, Vamsi Aribandi, Zhe Zhao, Yaguang Li, Zhao Chen, Donald Metzler, Heng Tze Cheng, Ed H. Chi. 8678-8690 [doi]
• Label-Descriptive Patterns and Their Application to Characterizing Classification ErrorsMichael A. Hedderich, Jonas Fischer, Dietrich Klakow, Jilles Vreeken. 8691-8707 [doi]
• NOMU: Neural Optimization-based Model UncertaintyJakob Heiss, Jakob Weissteiner, Hanna S. Wutte, Sven Seuken, Josef Teichmann. 8708-8758 [doi]
• Scaling Out-of-Distribution Detection for Real-World SettingsDan Hendrycks, Steven Basart, Mantas Mazeika, Andy Zou, Joseph Kwon, Mohammadreza Mostajabi, Jacob Steinhardt, Dawn Song. 8759-8773 [doi]
• Generalization Bounds using Lower Tail Exponents in Stochastic OptimizersLiam Hodgkinson, Umut Simsekli, Rajiv Khanna, Michael W. Mahoney. 8774-8795 [doi]
• Unsupervised Detection of Contextualized Embedding Bias with Application to IdeologyValentin Hofmann, Janet B. Pierrehumbert, Hinrich Schütze. 8796-8810 [doi]
• Neural Laplace: Learning diverse classes of differential equations in the Laplace domainSamuel Holt, Zhaozhi Qian, Mihaela van der Schaar. 8811-8832 [doi]
• Deep Hierarchy in BanditsJoey Hong, Branislav Kveton, Sumeet Katariya, Manzil Zaheer, Mohammad Ghavamzadeh. 8833-8851 [doi]
• DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated LearningRobert Hönig, Yiren Zhao, Robert Mullins. 8852-8866 [doi]
• Equivariant Diffusion for Molecule Generation in 3DEmiel Hoogeboom, Victor Garcia Satorras, Clément Vignac, Max Welling. 8867-8887 [doi]
• Conditional GANs with Auxiliary Discriminative ClassifierLiang Hou, Qi Cao, Huawei Shen, Siyuan Pan, Xiaoshuang Li, Xueqi Cheng. 8888-8902 [doi]
• AdAUC: End-to-end Adversarial AUC Optimization Against Long-tail ProblemsWenzheng Hou, Qianqian Xu, Zhiyong Yang 0001, Shilong Bao, Yuan He, Qingming Huang. 8903-8925 [doi]
• Wide Bayesian neural networks have a simple weight posterior: theory and accelerated samplingJiri Hron, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein. 8926-8945 [doi]
• Learning inverse folding from millions of predicted structuresChloe Hsu, Robert Verkuil, Jason Liu, Zeming Lin, Brian Hie, Tom Sercu, Adam Lerer, Alexander Rives. 8946-8970 [doi]
• Nearly Minimax Optimal Reinforcement Learning with Linear Function ApproximationPihe Hu, Yu Chen, Longbo Huang. 8971-9019 [doi]
• Neuron Dependency Graphs: A Causal Abstraction of Neural NetworksYaojie Hu, Jin Tian. 9020-9040 [doi]
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• Neural Network Poisson Models for Behavioural and Neural Spike Train DataMoein Khajehnejad, Forough Habibollahi, Richard Nock, Ehsan Arabzadeh, Peter Dayan, Amir Dezfouli. 10974-10996 [doi]
• Federated Reinforcement Learning: Linear Speedup Under Markovian SamplingSajad Khodadadian, Pranay Sharma, Gauri Joshi, Siva Theja Maguluri. 10997-11057 [doi]
• Multi-Level Branched Regularization for Federated LearningJinkyu Kim, Geeho Kim, Bohyung Han. 11058-11073 [doi]
• Learning fair representation with a parametric integral probability metricDongha Kim, Kunwoong Kim, Insung Kong, Ilsang Ohn, Yongdai Kim. 11074-11101 [doi]
• Dataset Condensation via Efficient Synthetic-Data ParameterizationJang-Hyun Kim, Jinuk Kim, Seong Joon Oh, Sangdoo Yun, Hwanjun Song, Joonhyun Jeong, Jung-Woo Ha 0001, Hyun Oh Song. 11102-11118 [doi]
• Guided-TTS: A Diffusion Model for Text-to-Speech via Classifier GuidanceHeeseung Kim, Sungwon Kim, Sungroh Yoon. 11119-11133 [doi]
• Variational On-the-Fly PersonalizationJangho Kim, Juntae Lee, Simyung Chang, Nojun Kwak. 11134-11147 [doi]
• Fisher SAM: Information Geometry and Sharpness Aware MinimisationMinyoung Kim, Da Li 0001, Shell Xu Hu, Timothy M. Hospedales. 11148-11161 [doi]
• ViT-NeT: Interpretable Vision Transformers with Neural Tree DecoderSangwon Kim, Jae Yeal Nam, ByoungChul Ko. 11162-11172 [doi]
• Sanity Simulations for Saliency MethodsJoon Sik Kim, Gregory Plumb, Ameet Talwalkar. 11173-11200 [doi]
• Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score EstimationDongjun Kim, SeungJae Shin, Kyungwoo Song, Wanmo Kang, Il-Chul Moon. 11201-11228 [doi]
• Rotting Infinitely Many-Armed BanditsJung Hun Kim, Milan Vojnovic, Se-Young Yun. 11229-11254 [doi]
• Accelerated Gradient Methods for Geodesically Convex Optimization: Tractable Algorithms and Convergence AnalysisJungbin Kim, Insoon Yang. 11255-11282 [doi]
• Generalizing to New Physical Systems via Context-Informed Dynamics ModelMatthieu Kirchmeyer, Yuan Yin, Jérémie Donà, Nicolas Baskiotis, Alain Rakotomamonjy, Patrick Gallinari. 11283-11301 [doi]
• SoQal: Selective Oracle Questioning for Consistency Based Active Learning of Cardiac SignalsDani Kiyasseh, Tingting Zhu 0001, David A. Clifton. 11302-11340 [doi]
• Curriculum Reinforcement Learning via Constrained Optimal TransportPascal Klink, Haoyi Yang, Carlo D'Eramo, Jan Peters 0001, Joni Pajarinen. 11341-11358 [doi]
• Exploiting Redundancy: Separable Group Convolutional Networks on Lie GroupsDavid M. Knigge, David W. Romero, Erik J. Bekkers. 11359-11386 [doi]
• Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated FrameworkChing Yun Ko, Jeet Mohapatra, Sijia Liu, Pin-Yu Chen, Luca Daniel, Lily Weng. 11387-11412 [doi]
• Transfer Learning In Differential Privacy's Hybrid-ModelRefael Kohen, Or Sheffet. 11413-11429 [doi]
• Markov Chain Monte Carlo for Continuous-Time Switching Dynamical SystemsLukas Köhs, Bastian Alt, Heinz Koeppl. 11430-11454 [doi]
• Partial disentanglement for domain adaptationLingjing Kong, Shaoan Xie, Weiran Yao, Yujia Zheng, Guangyi Chen, Petar Stojanov, Victor Akinwande, Kun Zhang 0001. 11455-11472 [doi]
• Simultaneously Learning Stochastic and Adversarial Bandits with General Graph FeedbackFang Kong 0002, Yichi Zhou, Shuai Li. 11473-11482 [doi]
• Adaptive Data Analysis with Correlated ObservationsAryeh Kontorovich, Menachem Sadigurschi, Uri Stemmer. 11483-11498 [doi]
• Controlling Conditional Language Models without Catastrophic ForgettingTomasz Korbak, Hady ElSahar, Germán Kruszewski, Marc Dymetman. 11499-11528 [doi]
• Batch Greenkhorn Algorithm for Entropic-Regularized Multimarginal Optimal Transport: Linear Rate of Convergence and Iteration ComplexityVladimir R. Kostic, Saverio Salzo, Massimiliano Pontil. 11529-11558 [doi]
• Certified Adversarial Robustness Under the Bounded Support SetYiwen Kou, Qinyuan Zheng, Yisen Wang. 11559-11597 [doi]
• Exact Learning of Preference Structure: Single-peaked Preferences and BeyondSonja Kraiczy, Edith Elkind. 11598-11612 [doi]
• Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time SeriesDaniel Kramer, Philine Lou Bommer, Daniel Durstewitz, Carlo Tombolini, Georgia Koppe. 11613-11633 [doi]
• Probabilistic ODE Solutions in Millions of DimensionsNicholas Krämer, Nathanael Bosch, Jonathan Schmidt, Philipp Hennig. 11634-11649 [doi]
• Active Nearest Neighbor Regression Through Delaunay RefinementAlexander Kravberg, Giovanni Luca Marchetti, Vladislav Polianskii, Anastasiia Varava, Florian T. Pokorny, Danica Kragic. 11650-11664 [doi]
• Functional Generalized Empirical Likelihood Estimation for Conditional Moment RestrictionsHeiner Kremer, Jia-Jie Zhu, Krikamol Muandet, Bernhard Schölkopf. 11665-11682 [doi]
• Calibrated and Sharp Uncertainties in Deep Learning via Density EstimationVolodymyr Kuleshov, Shachi Deshpande. 11683-11693 [doi]
• ActiveHedge: Hedge meets Active LearningBhuvesh Kumar, Jacob D. Abernethy, Venkatesh Saligrama. 11694-11709 [doi]
• Balancing Discriminability and Transferability for Source-Free Domain AdaptationJogendra Nath Kundu, Akshay R. Kulkarni, Suvaansh Bhambri, Deepesh Mehta, Shreyas Anand Kulkarni, Varun Jampani, Venkatesh Babu Radhakrishnan. 11710-11728 [doi]
• Showing Your Offline Reinforcement Learning Work: Online Evaluation Budget MattersVladislav Kurenkov, Sergey Kolesnikov. 11729-11752 [doi]
• Equivariant Priors for compressed sensing with unknown orientationAnna Kuzina, Kumar Pratik, Fabio Valerio Massoli, Arash Behboodi. 11753-11771 [doi]
• Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense MechanismsJeongyeol Kwon, Yonathan Efroni, Constantine Caramanis, Shie Mannor. 11772-11789 [doi]
• Large Batch Experience ReplayThibault Lahire, Matthieu Geist, Emmanuel Rachelson. 11790-11813 [doi]
• FedScale: Benchmarking Model and System Performance of Federated Learning at ScaleFan Lai, Yinwei Dai, Sanjay Sri Vallabh Singapuram, Jiachen Liu, Xiangfeng Zhu, Harsha V. Madhyastha, Mosharaf Chowdhury. 11814-11827 [doi]
• Smoothed Adaptive Weighting for Imbalanced Semi-Supervised Learning: Improve Reliability Against Unknown Distribution DataZhengfeng Lai, Chao Wang, Henrry Gunawan, Sen-Ching S. Cheung, Chen-Nee Chuah. 11828-11843 [doi]
• Functional Output Regression with Infimal Convolution: Exploring the Huber and ε-insensitive LossesAlex Lambert, Dimitri Bouche, Zoltán Szabó, Florence d'Alché-Buc. 11844-11867 [doi]
• Tell me why! Explanations support learning relational and causal structureAndrew K. Lampinen, Nicholas A. Roy, Ishita Dasgupta, Stephanie Cy Chan, Allison C. Tam, James L. McClelland, Chen Yan, Adam Santoro, Neil C. Rabinowitz, Jane X. Wang, Felix Hill. 11868-11890 [doi]
• Generative Cooperative Networks for Natural Language GenerationSylvain Lamprier, Thomas Scialom, Antoine Chaffin, Vincent Claveau, Ewa Kijak, Jacopo Staiano, Benjamin Piwowarski. 11891-11905 [doi]
• DSTAGNN: Dynamic Spatial-Temporal Aware Graph Neural Network for Traffic Flow ForecastingShiyong Lan, Yitong Ma, Weikang Huang, Wenwu Wang, Hongyu Yang, Pyang Li. 11906-11917 [doi]
• Cooperative Online Learning in Stochastic and Adversarial MDPsTal Lancewicki, Aviv Rosenberg 0002, Yishay Mansour. 11918-11968 [doi]
• PINs: Progressive Implicit Networks for Multi-Scale Neural RepresentationsZoe Landgraf, Alexander Sorkine-Hornung, Ricardo Silveira Cabral. 11969-11984 [doi]
• Co-training Improves Prompt-based Learning for Large Language ModelsHunter Lang, Monica N. Agrawal, Yoon Kim, David A. Sontag. 11985-12003 [doi]
• Goal Misgeneralization in Deep Reinforcement LearningLauro Langosco di Langosco, Jack Koch, Lee D. Sharkey, Jacob Pfau, David Krueger. 12004-12019 [doi]
• Marginal Tail-Adaptive Normalizing FlowsMike Laszkiewicz, Johannes Lederer, Asja Fischer. 12020-12048 [doi]
• Bregman Proximal Langevin Monte Carlo via Bregman-Moreau EnvelopesTim Tsz-Kit Lau, Han Liu. 12049-12077 [doi]
• Scalable Deep Reinforcement Learning Algorithms for Mean Field GamesMathieu Laurière, Sarah Perrin, Sertan Girgin, Paul Muller, Ayush Jain, Theophile Cabannes, Georgios Piliouras, Julien Pérolat, Romuald Elie, Olivier Pietquin, Matthieu Geist. 12078-12095 [doi]
• Implicit Bias of Linear Equivariant NetworksHannah Lawrence, Bobak Toussi Kiani, Kristian G. Georgiev, Andrew K. Dienes. 12096-12125 [doi]
• Differentially Private Maximal Information CoefficientsJohn Lazarsfeld, Aaron Johnson, Emmanuel Adéníran. 12126-12163 [doi]
• Entropic Gromov-Wasserstein between Gaussian DistributionsKhang Le, Dung Q. Le, Huy Nguyen, Dat Do, Tung Pham 0001, Nhat Ho. 12164-12203 [doi]
• Neurocoder: General-Purpose Computation Using Stored Neural ProgramsHung Le, Svetha Venkatesh. 12204-12221 [doi]
• Convergence of Policy Gradient for Entropy Regularized MDPs with Neural Network Approximation in the Mean-Field RegimeJames-Michael Leahy, Bekzhan Kerimkulov, David Siska, Lukasz Szpruch. 12222-12252 [doi]
• A Random Matrix Analysis of Data Stream Clustering: Coping With Limited Memory ResourcesHugo Lebeau, Romain Couillet, Florent Chatelain. 12253-12281 [doi]
• Neural Tangent Kernel Analysis of Deep Narrow Neural NetworksJongmin Lee, Joo-Young Choi, Ernest K. Ryu, Albert No. 12282-12351 [doi]
• Dataset Condensation with Contrastive SignalsSaehyung Lee, Sanghyuk Chun, Sangwon Jung, Sangdoo Yun, Sungroh Yoon. 12352-12364 [doi]
• Confidence Score for Source-Free Unsupervised Domain AdaptationJonghyun Lee 0004, Dahuin Jung, Junho Yim, Sungroh Yoon. 12365-12377 [doi]
• A Statistical Manifold Framework for Point Cloud DataYonghyeon Lee, Seungyeon Kim, Jinwon Choi, Frank Chongwoo Park. 12378-12402 [doi]
• Low-Complexity Deep Convolutional Neural Networks on Fully Homomorphic Encryption Using Multiplexed Parallel ConvolutionsEunsang Lee, Joon-Woo Lee, Junghyun Lee, Young-Sik Kim, Yongjune Kim 0001, Jong-Seon No, Woosuk Choi. 12403-12422 [doi]
• Statistical inference with implicit SGD: proximal Robbins-Monro vs. Polyak-RuppertYoonhyung Lee, Sungdong Lee, Joong-Ho Won. 12423-12454 [doi]
• Maslow's Hammer in Catastrophic Forgetting: Node Re-Use vs. Node ActivationSebastian Lee, Stefano Sarao Mannelli, Claudia Clopath, Sebastian Goldt, Andrew M. Saxe. 12455-12477 [doi]
• Query-Efficient and Scalable Black-Box Adversarial Attacks on Discrete Sequential Data via Bayesian OptimizationDeokjae Lee, Seungyong Moon, Junhyeok Lee, Hyun Oh Song. 12478-12497 [doi]
• Least Squares Estimation using Sketched Data with Heteroskedastic ErrorsSokbae Lee, Serena Ng. 12498-12520 [doi]
• Why the Rich Get Richer? On the Balancedness of Random Partition ModelsChangwoo J. Lee, Huiyan Sang. 12521-12541 [doi]
• Model Selection in Batch Policy Optimization