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math.OC2024
On the Convergence of Projected Policy Gradient for Any Constant Step Sizes
Jiacai Liu, Wenye Li, Dachao Lin +2
Projected policy gradient (PPG) is a basic policy optimization method in reinforcement learning. Given access to exact policy evaluations, previous studies have established the sub…
math.OC2024
On the Convergence of Policy in Unregularized Policy Mirror Descent
Dachao Lin, Zhihua Zhang
In this short note, we give the convergence analysis of the policy in the recent famous policy mirror descent (PMD). We mainly consider the unregularized setting following [11] wit…
math.OC2024
Anderson Acceleration Without Restart: A Novel Method with -Step Super Quadratic Convergence Rate
Haishan Ye, Dachao Lin, Xiangyu Chang +1
In this paper, we propose a novel Anderson's acceleration method to solve nonlinear equations, which does \emph{not} require a restart strategy to achieve numerical stability. We p…