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. 2212.05602
  4. Cited By
ResFed: Communication Efficient Federated Learning by Transmitting Deep
  Compressed Residuals

ResFed: Communication Efficient Federated Learning by Transmitting Deep Compressed Residuals

11 December 2022
Rui Song
Liguo Zhou
Lingjuan Lyu
Andreas Festag
Alois C. Knoll
    FedML
ArXivPDFHTML

Papers citing "ResFed: Communication Efficient Federated Learning by Transmitting Deep Compressed Residuals"

5 / 5 papers shown
Title
Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Models
Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Models
Weijiao Zhang
Jindong Han
Zhao Xu
Hang Ni
Hao Liu
Hui Xiong
Hui Xiong
AI4CE
77
15
0
30 Jan 2024
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions
Weiming Zhuang
Chen Chen
Lingjuan Lyu
C. L. P. Chen
Yaochu Jin
Lingjuan Lyu
AIFin
AI4CE
86
85
0
27 Jun 2023
An Information-Theoretic Justification for Model Pruning
An Information-Theoretic Justification for Model Pruning
Berivan Isik
Tsachy Weissman
Albert No
81
35
0
16 Feb 2021
Privacy and Robustness in Federated Learning: Attacks and Defenses
Privacy and Robustness in Federated Learning: Attacks and Defenses
Lingjuan Lyu
Han Yu
Xingjun Ma
Chen Chen
Lichao Sun
Jun Zhao
Qiang Yang
Philip S. Yu
FedML
169
351
0
07 Dec 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
157
758
0
28 Sep 2019
1