
SampleEfficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting
Lowcomplexity models such as linear function representation play a pivo...
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Softmax Policy Gradient Methods Can Take Exponential Time to Converge
The softmax policy gradient (PG) method, which performs gradient ascent ...
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Is QLearning Minimax Optimal? A Tight Sample Complexity Analysis
Qlearning, which seeks to learn the optimal Qfunction of a Markov deci...
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Derandomizing Knockoffs
ModelX knockoffs is a general procedure that can leverage any feature i...
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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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Randomized tests for highdimensional regression: A more efficient and powerful solution
We investigate the problem of testing the global null in the highdimens...
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The Lasso with general Gaussian designs with applications to hypothesis testing
The Lasso is a method for highdimensional regression, which is now comm...
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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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Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification
Adversarial robustness has become a fundamental requirement in modern ma...
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Sample Complexity of Asynchronous QLearning: Sharper Analysis and Variance Reduction
Asynchronous Qlearning aims to learn the optimal actionvalue function ...
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Breaking the Sample Size Barrier in ModelBased Reinforcement Learning with a Generative Model
We investigate the sample efficiency of reinforcement learning in a γdi...
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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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From Gauss to Kolmogorov: Localized Measures of Complexity for Ellipses
The Gaussian width is a fundamental quantity in probability, statistics ...
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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 highdimen...
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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 highdimen...
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Early stopping for kernel boosting algorithms: A general analysis with localized complexities
Early stopping of iterative algorithms is a widelyused form of regulari...
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Yuting Wei
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