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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 19: Proceedings of the 24th Annual Conference on Learning Theory, 9-11 June 2011, Budapest, Hungary

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Editors: Sham M. Kakade, Ulrike von Luxburg

[bib][citeproc]

Contents:

  • Preface
  • Accepted Papers

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Preface

Preface

; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:i-i

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Accepted Papers

Regret Bounds for the Adaptive Control of Linear Quadratic Systems

Yasin Abbasi-Yadkori, Csaba Szepesvári; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:1-26

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Blackwell Approachability and No-Regret Learning are Equivalent

Jacob Abernethy, Peter L. Bartlett, Elad Hazan; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:27-46

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Competitive Closeness Testing

Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:47-68

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Oracle inequalities for computationally budgeted model selection

Alekh Agarwal, John C. Duchi, Peter L. Bartlett, Clement Levrard; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:69-86

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Bandits, Query Learning, and the Haystack Dimension

Kareem Amin, Michael Kearns, Umar Syed; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:87-106

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Minimax Policies for Combinatorial Prediction Games

Jean-Yves Audibert, Sébastien Bubeck, Gábor Lugosi; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:107-132

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Minimax Regret of Finite Partial-Monitoring Games in Stochastic Environments

Gábor Bartók, Dávid Pál, Csaba Szepesvári; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:133-154

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Sample Complexity Bounds for Differentially Private Learning

Kamalika Chaudhuri, Daniel Hsu; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:155-186

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Tight conditions for consistent variable selection in high dimensional nonparametric regression

Laëtitia Comminges, Arnak S. Dalalyan; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:187-206

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Multiclass Learnability and the ERM principle

Amit Daniely, Sivan Sabato, Shai Ben-David, Shai Shalev-Shwartz; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:207-232

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Mixability is Bayes Risk Curvature Relative to Log Loss

Tim Erven, Mark D. Reid, Robert C. Williamson; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:233-252

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Distribution-Independent Evolvability of Linear Threshold Functions

Vitaly Feldman; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:253-272

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Lower Bounds and Hardness Amplification for Learning Shallow Monotone Formulas

Vitaly Feldman, Homin K. Lee, Rocco A. Servedio; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:273-292

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Complexity-Based Approach to Calibration with Checking Rules

Dean P. Foster, Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:293-314

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Concentration-Based Guarantees for Low-Rank Matrix Reconstruction

Rina Foygel, Nathan Srebro; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:315-340

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On the Consistency of Multi-Label Learning

Wei Gao, Zhi-Hua Zhou; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:341-358

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The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond

Aurélien Garivier, Olivier Cappé; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:359-376

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Sparsity Regret Bounds for Individual Sequences in Online Linear Regression

Sébastien Gerchinovitz; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:377-396

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Safe Learning: bridging the gap between Bayes, MDL and statistical learning theory via empirical convexity

Peter Grünwald; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:397-420

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Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization

Elad Hazan, Satyen Kale; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:421-436

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A Close Look to Margin Complexity and Related Parameters

Michael Kallweit, Hans Ulrich Simon; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:437-456

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Maximum Likelihood vs. Sequential Normalized Maximum Likelihood in On-line Density Estimation

Wojciech Kotłowski, Peter Grünwald; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:457-476

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A New Algorithm for Compressed Counting with Applications in Shannon Entropy Estimation in Dynamic Data

Ping Li, Cun-Hui Zhang; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:477-496

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A Finite-Time Analysis of Multi-armed Bandits Problems with Kullback-Leibler Divergences

Odalric-Ambrym Maillard, Rémi Munos, Gilles Stoltz; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:497-514

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Robust approachability and regret minimization in games with partial monitoring

Shie Mannor, Vianney Perchet, Gilles Stoltz; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:515-536

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The Rate of Convergence of Adaboost

Indraneel Mukherjee, Cynthia Rudin, Robert E. Schapire; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:537-558

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Online Learning: Beyond Regret

Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:559-594

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Neyman-Pearson classification under a strict constraint

Philippe Rigollet, Xin Tong; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:595-614

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Sequential Event Prediction with Association Rules

Cynthia Rudin, Benjamin Letham, Ansaf Salleb-Aouissi, Eugene Kogan, David Madigan; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:615-634

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Optimal aggregation of affine estimators

Joseph Salmon, Arnak Dalalyan; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:635-660

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Collaborative Filtering with the Trace Norm: Learning, Bounding, and Transducing

Ohad Shamir, Shai Shalev-Shwartz; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:661-678

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Contextual Bandits with Similarity Information

Aleksandrs Slivkins; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:679-702

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Adaptive Density Level Set Clustering

Ingo Steinwart; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:703-738

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Agnostic KWIK learning and efficient approximate reinforcement learning

István Szita, Csaba Szepesvári; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:739-772

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The Sample Complexity of Dictionary Learning

Daniel Vainsencher, Shie Mannor, Alfred M. Bruckstein; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:773-788

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Identifiability of Priors from Bounded Sample Sizes with Applications to Transfer Learning

Liu Yang, Steve Hanneke, Jaime Carbonell; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:789-806

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Does an Efficient Calibrated Forecasting Strategy Exist?

Jacob Abernethy, Shie Mannor; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:809-812

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Bounds on Individual Risk for Log-loss Predictors

Peter D. Grünwald, Wojciech Kotłowski; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:813-816

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A simple multi-armed bandit algorithm with optimal variation-bounded regret

Elad Hazan, Satyen Kale; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:817-820

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Minimax Algorithm for Learning Rotations

Wojciech Kotłowski, Manfred K. Warmuth; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:821-824

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Missing Information Impediments to Learnability

Loizos Michael; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:825-828

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Monotone multi-armed bandit allocations

Aleksandrs Slivkins; Proceedings of the 24th Annual Conference on Learning Theory, PMLR 19:829-834

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