A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation

6 June 2018

Papers citing "A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation"

50 / 223 papers shown

Title
Learning Optimal Admission Control in Partially Observable Queueing Networks Jonatha Anselmi B. Gaujal Louis-Sébastien Rebuffi 34 1 0 04 Aug 2023
Online covariance estimation for stochastic gradient descent under Markovian sampling Abhishek Roy Krishnakumar Balasubramanian 24 5 0 03 Aug 2023
Loss Dynamics of Temporal Difference Reinforcement Learning Blake Bordelon P. Masset Henry Kuo Cengiz Pehlevan AI4CE 21 0 0 10 Jul 2023
TD Convergence: An Optimization Perspective Kavosh Asadi Shoham Sabach Yao Liu Omer Gottesman Rasool Fakoor MU 20 8 0 30 Jun 2023
Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards Semih Cayci A. Eryilmaz 23 2 0 20 Jun 2023
Warm-Start Actor-Critic: From Approximation Error to Sub-optimality Gap Hang Wang Sen Lin Junshan Zhang OffRL OnRL 33 3 0 20 Jun 2023
Finite-Time Analysis of Minimax Q-Learning for Two-Player Zero-Sum Markov Games: Switching System Approach Dong-hwan Lee 21 2 0 09 Jun 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 30 7 0 30 May 2023
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities Aleksandr Beznosikov S. Samsonov Marina Sheshukova Alexander Gasnikov A. Naumov Eric Moulines 52 14 0 25 May 2023
Adaptive Policy Learning to Additional Tasks Wenjian Hao Zehui Lu Zihao Liang Tianyu Zhou Shaoshuai Mou 32 0 0 24 May 2023
Optimal Control of Nonlinear Systems with Unknown Dynamics Wenjian Hao Paulo Heredia Bowen Huang 42 1 0 24 May 2023
Federated TD Learning over Finite-Rate Erasure Channels: Linear Speedup under Markovian Sampling Nicolò Dal Fabbro A. Mitra George J. Pappas FedML 35 12 0 14 May 2023
Quantile-Based Deep Reinforcement Learning using Two-Timescale Policy Gradient Algorithms Jinyang Jiang Jiaqiao Hu Yijie Peng 18 2 0 12 May 2023
Streaming PCA for Markovian Data Syamantak Kumar Purnamrita Sarkar 50 6 0 03 May 2023
Concentration of Contractive Stochastic Approximation: Additive and Multiplicative Noise Zaiwei Chen S. T. Maguluri Martin Zubeldia 24 7 0 28 Mar 2023
n-Step Temporal Difference Learning with Optimal n Lakshmi Mandal S. Bhatnagar 29 2 0 13 Mar 2023
FaaSched: A Jitter-Aware Serverless Scheduler Abhisek Panda S. Sarangi 39 0 0 11 Mar 2023
Convergence Rates for Localized Actor-Critic in Networked Markov Potential Games Zhaoyi Zhou Zaiwei Chen Yiheng Lin Adam Wierman 46 7 0 08 Mar 2023
Policy Mirror Descent Inherently Explores Action Space Yan Li Guanghui Lan OffRL 58 8 0 08 Mar 2023
A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games Zaiwei Chen Kaipeng Zhang Eric Mazumdar Asuman Ozdaglar Adam Wierman 54 6 0 03 Mar 2023
Gauss-Newton Temporal Difference Learning with Nonlinear Function Approximation Zhifa Ke Junyu Zhang Zaiwen Wen 24 0 0 25 Feb 2023
Why Target Networks Stabilise Temporal Difference Methods Matt Fellows Matthew Smith Shimon Whiteson OOD AAML 21 7 0 24 Feb 2023
Stochastic Approximation Beyond Gradient for Signal Processing and Machine Learning Aymeric Dieuleveut G. Fort Eric Moulines Hoi-To Wai 59 12 0 22 Feb 2023
When Demonstrations Meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning Siliang Zeng Chenliang Li Alfredo García Min-Fong Hong OffRL 34 13 0 15 Feb 2023
Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity Han Wang A. Mitra Hamed Hassani George J. Pappas James Anderson FedML 31 21 0 04 Feb 2023
On the Statistical Benefits of Temporal Difference Learning David Cheikhi Daniel Russo 13 4 0 30 Jan 2023
Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic Wesley A Suttle Amrit Singh Bedi Bhrij Patel Brian M Sadler Alec Koppel Dinesh Manocha 29 14 0 28 Jan 2023
On The Convergence Of Policy Iteration-Based Reinforcement Learning With Monte Carlo Policy Evaluation Anna Winnicki R. Srikant 14 9 0 23 Jan 2023
Value Enhancement of Reinforcement Learning via Efficient and Robust Trust Region Optimization C. Shi Zhengling Qi Jianing Wang Fan Zhou OffRL 33 4 0 05 Jan 2023
Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning A. Mitra George J. Pappas Hamed Hassani 31 12 0 03 Jan 2023
Closing the gap between SVRG and TD-SVRG with Gradient Splitting Arsenii Mustafin Alexander Olshevsky I. Paschalidis 19 1 0 29 Nov 2022
Krylov-Bellman boosting: Super-linear policy evaluation in general state spaces Eric Xia Martin J. Wainwright OffRL 19 2 0 20 Oct 2022
Finite-time analysis of single-timescale actor-critic Xu-yang Chen Lin Zhao OffRL 29 21 0 18 Oct 2022
Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation Gandharv Patil Prashanth L.A. Dheeraj M. Nagaraj Doina Precup 11 15 0 12 Oct 2022
Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees Siliang Zeng Chenliang Li Alfredo García Min-Fong Hong 34 42 0 04 Oct 2022
Structural Estimation of Markov Decision Processes in High-Dimensional State Space with Finite-Time Guarantees Siliang Zeng Mingyi Hong Alfredo García OffRL 33 12 0 04 Oct 2022
Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes D. Huo Yudong Chen Qiaomin Xie 26 17 0 03 Oct 2022
Linear Convergence for Natural Policy Gradient with Log-linear Policy Parametrization Carlo Alfano Patrick Rebeschini 57 13 0 30 Sep 2022
Finite-Time Error Bounds for Greedy-GQ Yue Wang Yi Zhou Shaofeng Zou 34 1 0 06 Sep 2022
Global Convergence of Two-timescale Actor-Critic for Solving Linear Quadratic Regulator Xu-yang Chen Jingliang Duan Yingbin Liang Lin Zhao 32 6 0 18 Aug 2022
An Approximate Policy Iteration Viewpoint of Actor-Critic Algorithms Zaiwei Chen S. T. Maguluri 28 0 0 05 Aug 2022
Finite-Time Analysis of Asynchronous Q-learning under Diminishing Step-Size from Control-Theoretic View Han-Dong Lim Dong-hwan Lee 30 1 0 25 Jul 2022
Actor-Critic based Improper Reinforcement Learning Mohammadi Zaki Avinash Mohan Aditya Gopalan Shie Mannor 21 2 0 19 Jul 2022
Finite-time High-probability Bounds for Polyak-Ruppert Averaged Iterates of Linear Stochastic Approximation Alain Durmus Eric Moulines A. Naumov S. Samsonov 29 24 0 10 Jul 2022
Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data Abhishek Roy Krishnakumar Balasubramanian Saeed Ghadimi 16 9 0 22 Jun 2022
A Single-Timescale Analysis For Stochastic Approximation With Multiple Coupled Sequences Han Shen Tianyi Chen 47 15 0 21 Jun 2022
Finite-Time Analysis of Fully Decentralized Single-Timescale Actor-Critic Qijun Luo Xiao Li 32 1 0 12 Jun 2022
Stabilizing Q-learning with Linear Architectures for Provably Efficient Learning Andrea Zanette Martin J. Wainwright OOD 38 5 0 01 Jun 2022
Policy Gradient Method For Robust Reinforcement Learning Yue Wang Shaofeng Zou 81 69 0 15 May 2022
Stochastic first-order methods for average-reward Markov decision processes Tianjiao Li Feiyang Wu Guanghui Lan 27 14 0 11 May 2022