Variance-Reduced Off-Policy TDC Learning: Non-Asymptotic Convergence Analysis

26 October 2020

Papers citing "Variance-Reduced Off-Policy TDC Learning: Non-Asymptotic Convergence Analysis"

7 / 7 papers shown

Title
Central Limit Theorem for Two-Timescale Stochastic Approximation with Markovian Noise: Theory and Applications Jie Hu Vishwaraj Doshi Do Young Eun 38 4 0 17 Jan 2024
Finite-Time Error Bounds for Greedy-GQ Yue Wang Yi Zhou Shaofeng Zou 34 1 0 06 Sep 2022
Finite-Time Error Bounds for Distributed Linear Stochastic Approximation Yixuan Lin V. Gupta Ji Liu 32 3 0 24 Nov 2021
Online Robust Reinforcement Learning with Model Uncertainty Yue Wang Shaofeng Zou OOD OffRL 76 97 0 29 Sep 2021
Sample and Communication-Efficient Decentralized Actor-Critic Algorithms with Finite-Time Analysis Ziyi Chen Yi Zhou Rongrong Chen Shaofeng Zou 17 24 0 08 Sep 2021
A Multistep Lyapunov Approach for Finite-Time Analysis of Biased Stochastic Approximation Gang Wang Bingcong Li G. Giannakis 29 28 0 10 Sep 2019
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method Simon Lacoste-Julien Mark W. Schmidt Francis R. Bach 128 259 0 10 Dec 2012