On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration

9 April 2020

Papers citing "On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration"

23 / 23 papers shown

Title
A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression Yixuan Zhang Dongyan Yudong Chen Qiaomin Xie 26 0 0 11 Apr 2025
Sketched Adaptive Federated Deep Learning: A Sharp Convergence Analysis Zhijie Chen Qiaobo Li A. Banerjee FedML 35 0 0 11 Nov 2024
Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation Marina Sheshukova Denis Belomestny Alain Durmus Eric Moulines Alexey Naumov S. Samsonov 33 1 0 07 Oct 2024
Central Limit Theorem for Two-Timescale Stochastic Approximation with Markovian Noise: Theory and Applications Jie Hu Vishwaraj Doshi Do Young Eun 36 4 0 17 Jan 2024
Tight Finite Time Bounds of Two-Time-Scale Linear Stochastic Approximation with Markovian Noise Shaan ul Haque S. Khodadadian S. T. Maguluri 44 11 0 31 Dec 2023
Weighted Averaged Stochastic Gradient Descent: Asymptotic Normality and Optimality Ziyang Wei Wanrong Zhu Wei Biao Wu 27 3 0 13 Jul 2023
High-probability sample complexities for policy evaluation with linear function approximation Gen Li Weichen Wu Yuejie Chi Cong Ma Alessandro Rinaldo Yuting Wei OffRL 25 6 0 30 May 2023
Stability and Convergence of Distributed Stochastic Approximations with large Unbounded Stochastic Information Delays Adrian Redder Arunselvan Ramaswamy Holger Karl 17 1 0 11 May 2023
Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression Bhavya Agrawalla Krishnakumar Balasubramanian Promit Ghosal 25 2 0 20 Feb 2023
Efficiency Ordering of Stochastic Gradient Descent Jie Hu Vishwaraj Doshi Do Young Eun 31 6 0 15 Sep 2022
Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model Gen Li Yuejie Chi Yuting Wei Yuxin Chen 32 18 0 22 Aug 2022
A Single-Timescale Analysis For Stochastic Approximation With Multiple Coupled Sequences Han Shen Tianyi Chen 34 15 0 21 Jun 2022
Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming Sen Na Michael W. Mahoney 28 7 0 27 May 2022
A Statistical Analysis of Polyak-Ruppert Averaged Q-learning Xiang Li Wenhao Yang Jiadong Liang Zhihua Zhang Michael I. Jordan 37 15 0 29 Dec 2021
Gradient Temporal Difference with Momentum: Stability and Convergence Rohan Deb S. Bhatnagar 16 5 0 22 Nov 2021
Does Momentum Help? A Sample Complexity Analysis Swetha Ganesh Rohan Deb Gugan Thoppe A. Budhiraja 11 2 0 29 Oct 2021
Optimal policy evaluation using kernel-based temporal difference methods Yaqi Duan Mengdi Wang Martin J. Wainwright OffRL 20 26 0 24 Sep 2021
Online Bootstrap Inference For Policy Evaluation in Reinforcement Learning Pratik Ramprasad Yuantong Li Zhuoran Yang Zhaoran Wang W. Sun Guang Cheng OffRL 50 26 0 08 Aug 2021
Finite-Time Convergence Rates of Nonlinear Two-Time-Scale Stochastic Approximation under Markovian Noise Thinh T. Doan 8 15 0 04 Apr 2021
Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis Gen Li Changxiao Cai Ee Yuting Wei Yuejie Chi OffRL 37 75 0 12 Feb 2021
Optimal oracle inequalities for solving projected fixed-point equations Wenlong Mou A. Pananjady Martin J. Wainwright 16 14 0 09 Dec 2020
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model Gen Li Yuting Wei Yuejie Chi Yuxin Chen 31 124 0 26 May 2020
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 101 570 0 08 Dec 2012