Algorithmic Learning Theory 2024: Preface

Claire Vernade, Daniel Hsu; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:1-2

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A Mechanism for Sample-Efficient In-Context Learning for Sparse Retrieval Tasks

Jacob Abernethy, Alekh Agarwal, Teodor Vanislavov Marinov, Manfred K. Warmuth; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:3-46

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Mixtures of Gaussians are Privately Learnable with a Polynomial Number of Samples

Mohammad Afzali, Hassan Ashtiani, Christopher Liaw; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:47-73

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CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption

Shubhada Agrawal, Timothée Mathieu, Debabrota Basu, Odalric-Ambrym Maillard; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:74-124

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Semi-supervised Group DRO: Combating Sparsity with Unlabeled Data

Pranjal Awasthi, Satyen Kale, Ankit Pensia; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:125-160

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The Attractor of the Replicator Dynamic in Zero-Sum Games

Oliver Biggar, Iman Shames; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:161-178

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Tight Bounds for Local Glivenko-Cantelli

Moïse Blanchard, Vaclav Voracek; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:179-220

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Dueling Optimization with a Monotone Adversary

Avrim Blum, Meghal Gupta, Gene Li, Naren Sarayu Manoj, Aadirupa Saha, Yuanyuan Yang; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:221-243

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Online Recommendations for Agents with Discounted Adaptive Preferences

William Brown, Arpit Agarwal; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:244-281

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Distances for Markov Chains, and Their Differentiation

Tristan Brugère, Zhengchao Wan, Yusu Wang; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:282-336

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Concentration of empirical barycenters in metric spaces

Victor-Emmanuel Brunel, Jordan Serres; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:337-361

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Private PAC Learning May be Harder than Online Learning

Mark Bun, Aloni Cohen, Rathin Desai; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:362-389

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Not All Learnable Distribution Classes are Privately Learnable

Mark Bun, Gautam Kamath, Argyris Mouzakis, Vikrant Singhal; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:390-401

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Learning bounded-degree polytrees with known skeleton

Davin Choo, Joy Qiping Yang, Arnab Bhattacharyya, Clément L Canonne; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:402-443

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Near-continuous time Reinforcement Learning for continuous state-action spaces

Lorenzo Croissant, Marc Abeille, Bruno Bouchard; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:444-498

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Computation with Sequences of Assemblies in a Model of the Brain

Max Dabagia, Christos Papadimitriou, Santosh Vempala; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:499-504

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On the Sample Complexity of Two-Layer Networks: Lipschitz Vs. Element-Wise Lipschitz Activation

Amit Daniely, Elad Granot; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:505-517

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RedEx: Beyond Fixed Representation Methods via Convex Optimization

Amit Daniely, Mariano Schain, Gilad Yehudai; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:518-543

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The Dimension of Self-Directed Learning

Pramith Devulapalli, Steve Hanneke; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:544-573

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Learning Hypertrees From Shortest Path Queries

Shaun M Fallat, Valerii Maliuk, Seyed Ahmad Mojallal, Sandra Zilles; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:574-589

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Partially Interpretable Models with Guarantees on Coverage and Accuracy

Nave Frost, Zachary Lipton, Yishay Mansour, Michal Moshkovitz; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:590-613

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Importance-Weighted Offline Learning Done Right

Germano Gabbianelli, Gergely Neu, Matteo Papini; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:614-634

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The Impossibility of Parallelizing Boosting

Amin Karbasi, Kasper Green Larsen; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:635-653

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Agnostic Membership Query Learning with Nontrivial Savings: New Results and Techniques

Ari Karchmer; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:654-682

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Slowly Changing Adversarial Bandit Algorithms are Efficient for Discounted MDPs

Ian A. Kash, Lev Reyzin, Zishun Yu; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:683-718

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Efficient Agnostic Learning with Average Smoothness

Steve Hanneke, Aryeh Kontorovich, Guy Kornowski; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:719-731

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Provable Accelerated Convergence of Nesterov’s Momentum for Deep ReLU Neural Networks

Fangshuo Liao, Anastasios Kyrillidis; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:732-784

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Learning Spanning Forests Optimally in Weighted Undirected Graphs with CUT queries

Hang Liao, Deeparnab Chakrabarty; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:785-807

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Alternating minimization for generalized rank one matrix sensing: Sharp predictions from a random initialization

Kabir Aladin Verchand, Mengqi Lou, Ashwin Pananjady; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:808-809

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On the Computational Benefit of Multimodal Learning

Zhou Lu; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:810-821

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Predictor-Rejector Multi-Class Abstention: Theoretical Analysis and Algorithms

Anqi Mao, Mehryar Mohri, Yutao Zhong; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:822-867

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Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates

Michael Menart, Enayat Ullah, Raman Arora, Raef Bassily, Cristobal Guzman; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:868-906

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Adversarial Contextual Bandits Go Kernelized

Gergely Neu, Julia Olkhovskaya, Sattar Vakili; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:907-929

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Multiclass Learnability Does Not Imply Sample Compression

Chirag Pabbaraju; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:930-944

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Adversarial Online Collaborative Filtering

Stephen Pasteris, Fabio Vitale, Mark Herbster, Claudio Gentile, Andre Panisson; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:945-971

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The complexity of non-stationary reinforcement learning

Binghui Peng, Christos Papadimitriou; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:972-996

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Multiclass Online Learnability under Bandit Feedback

Ananth Raman, Vinod Raman, Unique Subedi, Idan Mehalel, Ambuj Tewari; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:997-1012

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Optimal Regret Bounds for Collaborative Learning in Bandits

Amitis Shidani, Sattar Vakili; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:1013-1029

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A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions

Vikrant Singhal; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:1030-1054

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Tight bounds for maximum $\ell_1$-margin classifiers

Stefan Stojanovic, Konstantin Donhauser, Fanny Yang; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:1055-1112

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Online Infinite-Dimensional Regression: Learning Linear Operators

Unique Subedi, Vinod Raman, Ambuj Tewari; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:1113-1133

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Universal Representation of Permutation-Invariant Functions on Vectors and Tensors

Puoya Tabaghi, Yusu Wang; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:1134-1187

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Adaptive Combinatorial Maximization: Beyond Approximate Greedy Policies

Shlomi Weitzman, Sivan Sabato; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:1188-1207

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Improving Adaptive Online Learning Using Refined Discretization

Zhiyu Zhang, Heng Yang, Ashok Cutkosky, Ioannis C Paschalidis; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:1208-1233

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Corruption-Robust Lipschitz Contextual Search

Shiliang Zuo; Proceedings of The 35th International Conference on Algorithmic Learning Theory, PMLR 237:1234-1254

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