Table of Contents

• Algorithmic Learning Theory 2023: Preface1-2 [doi]
• Variance-Reduced Conservative Policy IterationNaman Agarwal, Brian Bullins, Karan Singh. 3-33 [doi]
• Testing Tail Weight of a Distribution Via Hazard RateMaryam Aliakbarpour, Amartya Shankha Biswas, Kavya Ravichandran, Ronitt Rubinfeld. 34-81 [doi]
• Reconstructing Ultrametric Trees from Noisy ExperimentsEshwar Ram Arunachaleswaran, Anindya De, Sampath Kannan. 82-114 [doi]
• Adversarially Robust Learning with ToleranceHassan Ashtiani, Vinayak Pathak, Ruth Urner. 115-135 [doi]
• On Best-Arm Identification with a Fixed Budget in Non-Parametric Multi-Armed BanditsAntoine Barrier, Aurélien Garivier, Gilles Stoltz. 136-181 [doi]
• Robust Empirical Risk Minimization with ToleranceRobi Bhattacharjee, Max Hopkins, Akash Kumar 0010, Hantao Yu, Kamalika Chaudhuri. 182-203 [doi]
• Online k-means Clustering on Arbitrary Data StreamsRobi Bhattacharjee, Jacob Imola, Michal Moshkovitz, Sanjoy Dasgupta. 204-236 [doi]
• The Replicator Dynamic, Chain Components and the Response GraphOliver Biggar, Iman Shames. 237-258 [doi]
• A Query Algorithm for Learning a Spanning Forest in Weighted Undirected GraphsDeeparnab Chakrabarty, Hang Liao. 259-274 [doi]
• Spatially Adaptive Online Prediction of Piecewise Regular FunctionsSabyasachi Chatterjee, Subhajit Goswami. 275-309 [doi]
• Reaching Goals is Hard: Settling the Sample Complexity of the Stochastic Shortest PathLiyu Chen, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric. 310-357 [doi]
• On the complexity of finding stationary points of smooth functions in one dimensionSinho Chewi, Sébastien Bubeck, Adil Salim. 358-374 [doi]
• Fisher information lower bounds for samplingSinho Chewi, Patrik Gerber, Holden Lee, Chen Lu. 375-410 [doi]
• Robust Estimation of Discrete Distributions under Local Differential PrivacyJulien Chhor, Flore Sentenac. 411-446 [doi]
• Wide stochastic networks: Gaussian limit and PAC-Bayesian trainingEugenio Clerico, George Deligiannidis, Arnaud Doucet. 447-470 [doi]
• Pseudonorm Approachability and Applications to Regret MinimizationChristoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan. 471-509 [doi]
• A Unified Algorithm for Stochastic Path ProblemsChristoph Dann, Chen-Yu Wei, Julian Zimmert. 510-557 [doi]
• SQ Lower Bounds for Random Sparse Planted Vector ProblemJingqiu Ding, Yiding Hua. 558-596 [doi]
• On The Computational Complexity of Self-AttentionFeyza Duman Keles, Pruthuvi Mahesakya Wijewardena, Chinmay Hegde. 597-619 [doi]
• Online Learning with Off-Policy FeedbackGermano Gabbianelli, Gergely Neu, Matteo Papini. 620-641 [doi]
• Online Learning for Traffic Navigation in Congested NetworksSreenivas Gollapudi, Kostas Kollias, Chinmay Maheshwari, Manxi Wu. 642-662 [doi]
• Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex OptimizationMahdi Haghifam, Borja Rodríguez Gálvez, Ragnar Thobaben, Mikael Skoglund, Daniel M. Roy 0001, Gintare Karolina Dziugaite. 663-706 [doi]
• On Computable Online LearningNiki Hasrati, Shai Ben-David. 707-725 [doi]
• Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit ProblemsJunya Honda, Shinji Ito, Taira Tsuchiya. 726-754 [doi]
• Linear Reinforcement Learning with Ball Structure Action SpaceZeyu Jia, Randy Jia, Dhruv Madeka, Dean P. Foster. 755-775 [doi]
• Dealing with Unknown Variances in Best-Arm IdentificationMarc Jourdan, Rémy Degenne, Emilie Kaufmann. 776-849 [doi]
• Complexity Analysis of a Countable-armed Bandit ProblemAnand Kalvit, Assaf Zeevi. 850-890 [doi]
• Primal-Dual Algorithms with Predictions for Online Bounded Allocation and Ad-Auctions ProblemsEniko Kevi, Kim Thang Nguyen. 891-908 [doi]
• Max-Quantile Grouped Infinite-Arm BanditsIvan Lau, Yan Hao Ling, Mayank Shrivastava, Jonathan Scarlett. 909-945 [doi]
• Convergence of score-based generative modeling for general data distributionsHolden Lee, Jianfeng Lu 0001, Yixin Tan. 946-985 [doi]
• Private Stochastic Optimization with Large Worst-Case Lipschitz Parameter: Optimal Rates for (Non-Smooth) Convex Losses and Extension to Non-Convex LossesAndrew Lowy, Meisam Razaviyayn. 986-1054 [doi]
• Projection-free Adaptive Regret with Membership OraclesZhou Lu, Nataly Brukhim, Paula Gradu, Elad Hazan. 1055-1073 [doi]
• Improved High-Probability Regret for Adversarial Bandits with Time-Varying Feedback GraphsHaipeng Luo, Hanghang Tong, Mengxiao Zhang, Yuheng Zhang. 1074-1100 [doi]
• Efficient Global Planning in Large MDPs via Stochastic Primal-Dual OptimizationGergely Neu, Nneka Okolo. 1101-1123 [doi]
• Adversarial Online Multi-Task Reinforcement LearningQuan Nguyen, Nishant A. Mehta. 1124-1165 [doi]
• An Instance-Dependent Analysis for the Cooperative Multi-Player Multi-Armed BanditAldo Pacchiano, Peter L. Bartlett, Michael I. Jordan. 1166-1215 [doi]
• Towards Empirical Process Theory for Vector-Valued Functions: Metric Entropy of Smooth Function ClassesJunhyung Park, Krikamol Muandet. 1216-1260 [doi]
• Perceptronic Complexity and Online Matrix CompletionStephen Pasteris. 1261-1291 [doi]
• Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least SquaresAnant Raj, Melih Barsbey, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli. 1292-1342 [doi]
• Constant regret for sequence prediction with limited adviceEl Mehdi Saad, Gilles Blanchard. 1343-1386 [doi]
• Adaptive Power Method: Eigenvector Estimation from Sampled DataSeiyun Shin, Han Zhao, Ilan Shomorony. 1387-1410 [doi]
• Tournaments, Johnson Graphs and NC-TeachingHans-Ulrich Simon. 1411-1428 [doi]
• Implicit Regularization Towards Rank Minimization in ReLU NetworksNadav Timor, Gal Vardi, Ohad Shamir. 1429-1459 [doi]
• Optimistic PAC Reinforcement Learning: the Instance-Dependent ViewAndrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann. 1460-1480 [doi]
• Online Self-Concordant and Relatively Smooth Minimization, With Applications to Online Portfolio Selection and Learning Quantum StatesChung-En Tsai, Hao-Chung Cheng, Yen-Huan Li. 1481-1483 [doi]
• Best-of-Both-Worlds Algorithms for Partial MonitoringTaira Tsuchiya, Shinji Ito, Junya Honda. 1484-1515 [doi]
• Dictionary Learning for the Almost-Linear Sparsity RegimeAlexei Novikov, Stephen White. 1516-1554 [doi]
• Universal Bias Reduction in Estimation of Smooth Additive Function in High DimensionsFan Zhou, Ping Li, Cun-Hui Zhang. 1555-1578 [doi]