Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity

4 February 2023

Han Wang

A. Mitra

Hamed Hassani

George J. Pappas

James Anderson

FedML

ArXiv PDF HTML

Papers citing "Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity"

22 / 22 papers shown

Title
Achieving Tighter Finite-Time Rates for Heterogeneous Federated Stochastic Approximation under Markovian Sampling Feng Zhu Aritra Mitra Robert W. Heath FedML 36 0 0 15 Apr 2025
On the Linear Speedup of Personalized Federated Reinforcement Learning with Shared Representations Guojun Xiong Shufan Wang Daniel Jiang Jian Li FedML 73 1 0 22 Nov 2024
Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in Unified Distributed SGD Jie Hu Yi-Ting Ma Do Young Eun FedML 27 0 0 26 Sep 2024
Towards Fast Rates for Federated and Multi-Task Reinforcement Learning Feng Zhu Robert W. Heath Jr. Aritra Mitra 24 1 0 09 Sep 2024
On the Convergence Rates of Federated Q-Learning across Heterogeneous Environments Muxing Wang Pengkun Yang Lili Su FedML 19 1 0 05 Sep 2024
Finite-Time Analysis of Asynchronous Multi-Agent TD Learning Nicolò Dal Fabbro Arman Adibi Aritra Mitra George J. Pappas 24 1 0 29 Jul 2024
Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments Han Wang Sihong He Zhili Zhang Fei Miao James Anderson 39 3 0 29 May 2024
Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis Guangchen Lan Dong-Jun Han Abolfazl Hashemi Vaneet Aggarwal Christopher G. Brinton 122 15 0 09 Apr 2024
Compressed Federated Reinforcement Learning with a Generative Model Ali Beikmohammadi Sarit Khirirat Sindri Magnússon FedML 30 2 0 26 Mar 2024
DASA: Delay-Adaptive Multi-Agent Stochastic Approximation Nicolò Dal Fabbro Arman Adibi H. Vincent Poor Sanjeev R. Kulkarni A. Mitra George J. Pappas 28 2 0 25 Mar 2024
Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries Swetha Ganesh Jiayu Chen Gugan Thoppe Vaneet Aggarwal FedML 50 1 0 15 Mar 2024
One-Shot Averaging for Distributed TD( $λ$ ) Under Markov Sampling Haoxing Tian I. Paschalidis Alexander Olshevsky OffRL 31 3 0 13 Mar 2024
A Simple Finite-Time Analysis of TD Learning with Linear Function Approximation Aritra Mitra 18 3 0 04 Mar 2024
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling Arman Adibi Nicolò Dal Fabbro Luca Schenato Sanjeev R. Kulkarni H. Vincent Poor George J. Pappas Hamed Hassani A. Mitra 22 8 0 19 Feb 2024
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices Jiin Woo Laixi Shi Gauri Joshi Yuejie Chi OffRL 24 3 0 08 Feb 2024
SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning Paul Mangold S. Samsonov Safwan Labbi I. Levin Réda Alami Alexey Naumov Eric Moulines 27 1 0 06 Feb 2024
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning Chenyu Zhang Han Wang Aritra Mitra James Anderson 21 18 0 27 Jan 2024
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates Guangchen Lan Han Wang James Anderson Christopher G. Brinton Vaneet Aggarwal FedML 19 27 0 09 Oct 2023
Federated TD Learning over Finite-Rate Erasure Channels: Linear Speedup under Markovian Sampling Nicolò Dal Fabbro A. Mitra George J. Pappas FedML 22 12 0 14 May 2023
Towards Personalized Federated Learning A. Tan Han Yu Li-zhen Cui Qiang Yang FedML AI4CE 183 840 0 01 Mar 2021
Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients A. Mitra Rayana H. Jaafar George J. Pappas Hamed Hassani FedML 55 157 0 14 Feb 2021
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization Amirhossein Reisizadeh Aryan Mokhtari Hamed Hassani Ali Jadbabaie Ramtin Pedarsani FedML 157 758 0 28 Sep 2019