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06/15/2023
Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models
Diffusion models, which convert noise into new data instances by learnin...
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05/30/2023
Sharp high-probability sample complexities for policy evaluation with linear function approximation
This paper is concerned with the problem of policy evaluation with linea...
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05/26/2023
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model
This paper investigates model robustness in reinforcement learning (RL) ...
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02/07/2023
Approximate message passing from random initialization with applications to ℤ_2 synchronization
This paper is concerned with the problem of reconstructing an unknown ra...
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08/22/2022
Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model
This paper studies multi-agent reinforcement learning in Markov games, w...
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08/05/2022
A Non-Asymptotic Framework for Approximate Message Passing in Spiked Models
Approximate message passing (AMP) emerges as an effective iterative para...
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05/25/2022
Mitigating multiple descents: A model-agnostic framework for risk monotonization
Recent empirical and theoretical analyses of several commonly used predi...
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04/11/2022
Settling the Sample Complexity of Model-Based Offline Reinforcement Learning
This paper is concerned with offline reinforcement learning (RL), which ...
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02/28/2022
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity
Offline or batch reinforcement learning seeks to learn a near-optimal po...
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10/18/2021
Minimum ℓ_1-norm interpolators: Precise asymptotics and multiple descent
An evolving line of machine learning works observe empirical evidence th...
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05/31/2021
Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization
This paper investigates the problem of computing the equilibrium of comp...
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05/17/2021
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting
Low-complexity models such as linear function representation play a pivo...
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02/22/2021
Softmax Policy Gradient Methods Can Take Exponential Time to Converge
The softmax policy gradient (PG) method, which performs gradient ascent ...
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02/12/2021
Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
Q-learning, which seeks to learn the optimal Q-function of a Markov deci...
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12/04/2020
Derandomizing Knockoffs
Model-X knockoffs is a general procedure that can leverage any feature i...
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12/01/2020
Debiasing Evaluations That are Biased by Evaluations
It is common to evaluate a set of items by soliciting people to rate the...
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10/03/2020
Randomized tests for high-dimensional regression: A more efficient and powerful solution
We investigate the problem of testing the global null in the high-dimens...
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07/27/2020
The Lasso with general Gaussian designs with applications to hypothesis testing
The Lasso is a method for high-dimensional regression, which is now comm...
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07/13/2020
Fast Global Convergence of Natural Policy Gradient Methods with Entropy Regularization
Natural policy gradient (NPG) methods are among the most widely used pol...
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06/29/2020
Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification
Adversarial robustness has become a fundamental requirement in modern ma...
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06/04/2020
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction
Asynchronous Q-learning aims to learn the optimal action-value function ...
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05/26/2020
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model
We investigate the sample efficiency of reinforcement learning in a γ-di...
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01/14/2020
Inference for linear forms of eigenvectors under minimal eigenvalue separation: Asymmetry and heteroscedasticity
A fundamental task that spans numerous applications is inference and unc...
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03/21/2018
From Gauss to Kolmogorov: Localized Measures of Complexity for Ellipses
The Gaussian width is a fundamental quantity in probability, statistics ...
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12/03/2017
The local geometry of testing in ellipses: Tight control via localized Kolmogorov widths
We study the local geometry of testing a mean vector within a high-dimen...
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12/03/2017
The local geometry of testing in ellipses: Tight control via localized Kolomogorov widths
We study the local geometry of testing a mean vector within a high-dimen...
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07/05/2017
