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06/05/2023
The L^∞ Learnability of Reproducing Kernel Hilbert Spaces
In this work, we analyze the learnability of reproducing kernel Hilbert ...
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05/09/2023
A duality framework for generalization analysis of random feature models and two-layer neural networks
We consider the problem of learning functions in the ℱ_p,π and Barron sp...
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02/20/2023
Reinforcement Learning with Function Approximation: From Linear to Nonlinear
Function approximation has been an indispensable component in modern rei...
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04/25/2022
Learning High-Dimensional McKean-Vlasov Forward-Backward Stochastic Differential Equations with General Distribution Dependence
One of the core problems in mean-field control and mean-field games is t...
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11/05/2021
Perturbational Complexity by Distribution Mismatch: A Systematic Analysis of Reinforcement Learning in Reproducing Kernel Hilbert Space
Most existing theoretical analysis of reinforcement learning (RL) is lim...
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08/10/2021
Linear approximability of two-layer neural networks: A comprehensive analysis based on spectral decay
In this paper, we present a spectral-based approach to study the linear ...
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04/24/2021
A Class of Dimensionality-free Metrics for the Convergence of Empirical Measures
This paper concerns the convergence of empirical measures in high dimens...
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04/15/2021
An L^2 Analysis of Reinforcement Learning in High Dimensions with Kernel and Neural Network Approximation
Reinforcement learning (RL) algorithms based on high-dimensional functio...
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08/12/2020
Convergence of Deep Fictitious Play for Stochastic Differential Games
Stochastic differential games have been used extensively to model agents...
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11/03/2018