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Proceedings of Machine Learning Research

Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research
Proceedings of Machine Learning Research
PMLR · 2026-06-02 · via Proceedings of Machine Learning Research

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Volume 237: International Conference on Algorithmic Learning Theory, 25-28 February 2024, La Jolla, California, USA

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Editors: Claire Vernade, Daniel Hsu

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Filter Authors: Filter Titles:

Algorithmic Learning Theory 2024: Preface

; 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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此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。