The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond

18 May 2023

Papers citing "The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond"

6 / 6 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
FedRLHF: A Convergence-Guaranteed Federated Framework for Privacy-Preserving and Personalized RLHF Flint Xiaofeng Fan Cheston Tan Yew-Soon Ong Roger Wattenhofer Wei Tsang Ooi 85 1 0 20 Dec 2024
SwiftRL: Towards Efficient Reinforcement Learning on Real Processing-In-Memory Systems Kailash Gogineni Sai Santosh Dayapule Juan Gómez Luna Karthikeya Gogineni Peng Wei Tian-Shing Lan Mohammad Sadrosadati Onur Mutlu Guru Venkataramani 50 10 0 07 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 Brinton 124 15 0 09 Apr 2024
CAESAR: Enhancing Federated RL in Heterogeneous MDPs through Convergence-Aware Sampling with Screening Hei Yi Mak Flint Xiaofeng Fan Luca A. Lanzendörfer Cheston Tan Wei Tsang Ooi Roger Wattenhofer FedML 32 2 0 29 Mar 2024
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices Jiin Woo Laixi Shi Gauri Joshi Yuejie Chi OffRL 29 3 0 08 Feb 2024