ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2301.11135
  4. Cited By
FedHQL: Federated Heterogeneous Q-Learning

FedHQL: Federated Heterogeneous Q-Learning

26 January 2023
Flint Xiaofeng Fan
Yining Ma
Zhongxiang Dai
Cheston Tan
Bryan Kian Hsiang Low
Roger Wattenhofer
    FedML
ArXivPDFHTML

Papers citing "FedHQL: Federated Heterogeneous Q-Learning"

10 / 10 papers shown
Title
Federated Reinforcement Learning with Environment Heterogeneity
Federated Reinforcement Learning with Environment Heterogeneity
Hao Jin
Yang Peng
Wenhao Yang
Shusen Wang
Zhihua Zhang
82
74
0
06 Apr 2022
Fault-Tolerant Federated Reinforcement Learning with Theoretical
  Guarantee
Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee
Flint Xiaofeng Fan
Yining Ma
Zhongxiang Dai
Wei Jing
Cheston Tan
K. H. Low
FedML
AI4CE
57
79
0
26 Oct 2021
When Deep Reinforcement Learning Meets Federated Learning: Intelligent
  Multi-Timescale Resource Management for Multi-access Edge Computing in 5G
  Ultra Dense Network
When Deep Reinforcement Learning Meets Federated Learning: Intelligent Multi-Timescale Resource Management for Multi-access Edge Computing in 5G Ultra Dense Network
Shuai Yu
Xu Chen
Zhi Zhou
Xiaowen Gong
Di Wu
46
216
0
22 Sep 2020
Advances and Open Problems in Federated Learning
Advances and Open Problems in Federated Learning
Peter Kairouz
H. B. McMahan
Brendan Avent
A. Bellet
M. Bennis
...
Zheng Xu
Qiang Yang
Felix X. Yu
Han Yu
Sen Zhao
FedML
AI4CE
223
6,247
0
10 Dec 2019
Distributed Prioritized Experience Replay
Distributed Prioritized Experience Replay
Dan Horgan
John Quan
David Budden
Gabriel Barth-Maron
Matteo Hessel
H. V. Hasselt
David Silver
145
740
0
02 Mar 2018
IMPALA: Scalable Distributed Deep-RL with Importance Weighted
  Actor-Learner Architectures
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
L. Espeholt
Hubert Soyer
Rémi Munos
Karen Simonyan
Volodymyr Mnih
...
Vlad Firoiu
Tim Harley
Iain Dunning
Shane Legg
Koray Kavukcuoglu
204
1,598
0
05 Feb 2018
Federated Optimization: Distributed Machine Learning for On-Device
  Intelligence
Federated Optimization: Distributed Machine Learning for On-Device Intelligence
Jakub Konecný
H. B. McMahan
Daniel Ramage
Peter Richtárik
FedML
126
1,897
0
08 Oct 2016
Asynchronous Methods for Deep Reinforcement Learning
Asynchronous Methods for Deep Reinforcement Learning
Volodymyr Mnih
Adria Puigdomenech Badia
M. Berk Mirza
Alex Graves
Timothy Lillicrap
Tim Harley
David Silver
Koray Kavukcuoglu
191
8,850
0
04 Feb 2016
Massively Parallel Methods for Deep Reinforcement Learning
Massively Parallel Methods for Deep Reinforcement Learning
Arun Nair
Praveen Srinivasan
Sam Blackwell
Cagdas Alcicek
Rory Fearon
...
Stig Petersen
Shane Legg
Volodymyr Mnih
Koray Kavukcuoglu
David Silver
OffRL
AI4CE
GNN
89
503
0
15 Jul 2015
Playing Atari with Deep Reinforcement Learning
Playing Atari with Deep Reinforcement Learning
Volodymyr Mnih
Koray Kavukcuoglu
David Silver
Alex Graves
Ioannis Antonoglou
Daan Wierstra
Martin Riedmiller
119
12,223
0
19 Dec 2013
1