Articles by Alexander Rakhlin

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Random Latent Exploration for Deep Reinforcement Learning

27 February 2025 by Srinath Mahankali and others

Machine Learning

Refined Risk Bounds for Unbounded Losses via Transductive Priors

21 February 2025 by Jian Qian and others

Machine Learning, Statistics Theory

Near-Optimal Private Learning in Linear Contextual Bandits

18 February 2025 by Fan Chen and others

Machine Learning, Artificial Intelligence

Do We Need to Verify Step by Step? Rethinking Process Supervision from a Theoretical Perspective

14 February 2025 by Zeyu Jia and others

Machine Learning, Artificial Intelligence

Rate of convergence of the smoothed empirical Wasserstein distance

9 February 2025 by Adam Block and others

Probability, Information Theory

Decision Making in Changing Environments: Robustness, Query-Based Learning, and Differential Privacy

24 January 2025 by Fan Chen and Alexander Rakhlin

Machine Learning, Artificial Intelligence

Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability

6 December 2024 by Fan Chen and others

Machine Learning, Information Theory

How Does Variance Shape the Regret in Contextual Bandits?

27 November 2024 by Zeyu Jia and others

Machine Learning

Near-Optimal Learning and Planning in Separated Latent MDPs

12 June 2024 by Fan Chen and others

Machine Learning, Artificial Intelligence

Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF

31 May 2024 by Tengyang Xie and others at

Microsoft Research

Machine Learning, Artificial Intelligence

The Power of Resets in Online Reinforcement Learning

26 April 2024 by Zakaria Mhammedi and others

Machine Learning, Artificial Intelligence

Online Estimation via Offline Estimation: An Information-Theoretic Framework

15 April 2024 by Dylan Foster and others

Machine Learning, Statistics Theory

Offline Reinforcement Learning: Role of State Aggregation and Trajectory Data

25 March 2024 by Zeyu Jia and others

Machine Learning, Artificial Intelligence

Oracle-Efficient Smoothed Online Learning for Piecewise Continuous Decision Making

19 March 2024 by Adam Block and others

Machine Learning

Efficient Model-Free Exploration in Low-Rank MDPs

29 February 2024 by Zakaria Mhammedi and others

Machine Learning, Optimization and Control

On the Performance of Empirical Risk Minimization with Smoothed Data

22 February 2024 by Adam Block and others

Machine Learning

Foundations of Reinforcement Learning and Interactive Decision Making

27 December 2023 by Dylan Foster and Alexander Rakhlin

Machine Learning, Optimization and Control

Convergence of Adam Under Relaxed Assumptions

7 November 2023 by Haochuan Li and others

Optimization and Control, Machine Learning

Convex and Non-convex Optimization Under Generalized Smoothness

3 November 2023 by Haochuan Li and others

Optimization and Control, Machine Learning

When is Agnostic Reinforcement Learning Statistically Tractable?

9 October 2023 by Zeyu Jia and others

Machine Learning, Artificial Intelligence

Model-Free Reinforcement Learning with the Decision-Estimation Coefficient

12 August 2023 by Dylan Foster and others

Machine Learning, Optimization and Control

Tight Bounds for γ-Regret via the Decision-Estimation Coefficient

21 July 2023 by Margalit Glasgow and Alexander Rakhlin

Machine Learning

On the Variance, Admissibility, and Stability of Empirical Risk Minimization

29 May 2023 by Gil Kur and others

Statistics Theory, Machine Learning

On the Complexity of Multi-Agent Decision Making: From Learning in Games to Partial Monitoring

1 May 2023 by Dylan Foster and others

Machine Learning, Artificial Intelligence

Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL

12 April 2023 by Zakaria Mhammedi and others

Machine Learning, Artificial Intelligence

On the Complexity of Adversarial Decision Making

27 June 2022 by Dylan Foster and others

Machine Learning, Optimization and Control

Intrinsic Dimension Estimation Using Wasserstein Distances

31 May 2022 by Adam Block and others

Machine Learning

The Statistical Complexity of Interactive Decision Making

23 April 2022 by Dylan Foster and others

Machine Learning, Optimization and Control

Smoothed Online Learning is as Easy as Statistical Learning

7 March 2022 by Adam Block and others

Machine Learning

Damped Online Newton Step for Portfolio Selection

15 February 2022 by Zakaria Mhammedi and Alexander Rakhlin

Machine Learning, Optimization and Control

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Machine Learning Statistics Theory Optimization and Control Artificial Intelligence Information Theory Computer Science and Game Theory Systems and Control Computer Vision and Pattern Recognition Probability Social and Information Networks Computational Complexity Computation and Language Multiagent Systems Computational Geometry Metric Geometry