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. 2309.15659
  4. Cited By
Federated Deep Equilibrium Learning: A Compact Shared Representation for
  Edge Communication Efficiency

Federated Deep Equilibrium Learning: A Compact Shared Representation for Edge Communication Efficiency

27 September 2023
Long Tan Le
Tuan Dung Nguyen
Tung-Anh Nguyen
Choong Seon Hong
Nguyen H. Tran
    FedML
ArXivPDFHTML

Papers citing "Federated Deep Equilibrium Learning: A Compact Shared Representation for Edge Communication Efficiency"

4 / 4 papers shown
Title
Communication-Efficient ADMM-based Federated Learning
Communication-Efficient ADMM-based Federated Learning
Shenglong Zhou
Geoffrey Ye Li
FedML
35
22
0
28 Oct 2021
Towards Personalized Federated Learning
Towards Personalized Federated Learning
A. Tan
Han Yu
Li-zhen Cui
Qiang Yang
FedML
AI4CE
209
840
0
01 Mar 2021
Adaptive Personalized Federated Learning
Adaptive Personalized Federated Learning
Yuyang Deng
Mohammad Mahdi Kamani
M. Mahdavi
FedML
212
542
0
30 Mar 2020
FedPAQ: A Communication-Efficient Federated Learning Method with
  Periodic Averaging and Quantization
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization
Amirhossein Reisizadeh
Aryan Mokhtari
Hamed Hassani
Ali Jadbabaie
Ramtin Pedarsani
FedML
174
760
0
28 Sep 2019
1