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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 98: Algorithmic Learning Theory, 22-24 March 2019, Chicago, Illinois

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Editors: Aurélien Garivier, Satyen Kale

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Filter Authors: Filter Titles:

Algorithmic Learning Theory 2019: Preface

; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:1-2

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On Learning Graphs with Edge-Detecting Queries

Hasan Abasi, Bshouty Nader; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:3-30

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An Exponential Efron-Stein Inequality for $L_q$ Stable Learning Rules

Karim Abou-Moustafa, Csaba Szepesvári; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:31-63

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Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach

Mastane Achab, Anna Korba, Stephan Clémençon; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:64-93

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A minimax near-optimal algorithm for adaptive rejection sampling

Juliette Achddou, Joseph Lam-Weil, Alexandra Carpentier, Gilles Blanchard; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:94-126

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Attribute-efficient learning of monomials over highly-correlated variables

Alexandr Andoni, Rishabh Dudeja, Daniel Hsu, Kiran Vodrahalli; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:127-161

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Improved Generalization Bounds for Robust Learning

Idan Attias, Aryeh Kontorovich, Yishay Mansour; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:162-183

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A simple parameter-free and adaptive approach to optimization under a minimal local smoothness assumption

Peter L. Bartlett, Victor Gabillon, Michal Valko; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:184-206

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Adaptive Exact Learning of Decision Trees from Membership Queries

Nader H. Bshouty, Catherine A. Haddad-Zaknoon; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:207-234

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Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning

Brian Bullins, Elad Hazan, Adam Kalai, Roi Livni; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:235-246

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Dynamic Pricing with Finitely Many Unknown Valuations

Nicolò Cesa-Bianchi, Tommaso Cesari, Vianney Perchet; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:247-273

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Online Non-Additive Path Learning under Full and Partial Information

Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Holakou Rahmanian, Manfred Warmuth; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:274-299

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Two-Player Games for Efficient Non-Convex Constrained Optimization

Andrew Cotter, Heinrich Jiang, Karthik Sridharan; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:300-332

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Competitive ratio vs regret minimization: achieving the best of both worlds

Amit Daniely, Yishay Mansour; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:333-368

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Hardness of Improper One-Sided Learning of Conjunctions For All Uniformly Falsifiable CSPs

Alexander Durgin, Brendan Juba; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:369-382

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Limit Learning Equivalence Structures

Ekaterina Fokina, Timo Kötzing, Luca San Mauro; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:383-403

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Uniform regret bounds over $\mathbb{R}^d$ for the sequential linear regression problem with the square loss

Pierre Gaillard, Sébastien Gerchinovitz, Malo Huard, Gilles Stoltz; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:404-432

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A tight excess risk bound via a unified PAC-Bayesian–Rademacher–Shtarkov–MDL complexity

Peter D. Grünwald, Nishant A. Mehta; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:433-465

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Sample Compression for Real-Valued Learners

Steve Hanneke, Aryeh Kontorovich, Menachem Sadigurschi; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:466-488

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A Sharp Lower Bound for Agnostic Learning with Sample Compression Schemes

Steve Hanneke, Aryeh Kontorovich; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:489-505

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Optimal Collusion-Free Teaching

David Kirkpatrick, Hans U. Simon, Sandra Zilles; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:506-528

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Cleaning up the neighborhood: A full classification for adversarial partial monitoring

Tor Lattimore, Csaba Szepesvári; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:529-556

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Online Influence Maximization with Local Observations

Gábor Lugosi, Gergely Neu, Julia Olkhovskaya; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:557-580

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Can Adversarially Robust Learning LeverageComputational Hardness?

Saeed Mahloujifar, Mohammad Mahmoody; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:581-609

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Sequential change-point detection: Laplace concentration of scan statistics and non-asymptotic delay bounds

Odalric-Ambrym Maillard; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:610-632

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Average-Case Information Complexity of Learning

Ido Nachum, Amir Yehudayoff; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:633-646

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Interplay of minimax estimation and minimax support recovery under sparsity

Mohamed Ndaoud; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:647-668

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Ising Models with Latent Conditional Gaussian Variables

Frank Nussbaum, Joachim Giesen; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:669-681

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Exploiting geometric structure in mixture proportion estimation with generalised Blanchard-Lee-Scott estimators

Henry Reeve, Ata Kabán; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:682-699

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PAC Battling Bandits in the Plackett-Luce Model

Aadirupa Saha, Aditya Gopalan; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:700-737

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A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation

Clayton Scott; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:738-761

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General parallel optimization a without metric

Xuedong Shang, Emilie Kaufmann, Michal Valko; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:762-788

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Old Techniques in Differentially Private Linear Regression

Or Sheffet; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:789-827

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PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review

Ivan Stelmakh, Nihar B. Shah, Aarti Singh; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:828-856

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Stochastic Nonconvex Optimization with Large Minibatches

Weiran Wang, Nathan Srebro; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:857-882

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Online Linear Optimization with Sparsity Constraints

Jun-Kun Wang, Chi-Jen Lu, Shou-De Lin; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:883-897

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Noninteractive Locally Private Learning of Linear Models via Polynomial Approximations

Di Wang, Adam Smith, Jinhui Xu; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:898-903

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Minimax Learning of Ergodic Markov Chains

Geoffrey Wolfer, Aryeh Kontorovich; Proceedings of the 30th International Conference on Algorithmic Learning Theory, PMLR 98:904-930

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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。