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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"

8 / 8 papers shown
Title
Anatomical 3D Style Transfer Enabling Efficient Federated Learning with
  Extremely Low Communication Costs
Anatomical 3D Style Transfer Enabling Efficient Federated Learning with Extremely Low Communication Costs
Yuto Shibata
Yasunori Kudo
Yohei Sugawara
21
0
0
26 Oct 2024
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
Cheng Chen
Yaochu Jin
Lingjuan Lyu
AIFin
AI4CE
99
85
0
27 Jun 2023
FedBEVT: Federated Learning Bird's Eye View Perception Transformer in
  Road Traffic Systems
FedBEVT: Federated Learning Bird's Eye View Perception Transformer in Road Traffic Systems
Rui Song
Runsheng Xu
Andreas Festag
Jiaqi Ma
Alois C. Knoll
FedML
28
25
0
04 Apr 2023
Federated Learning via Decentralized Dataset Distillation in
  Resource-Constrained Edge Environments
Federated Learning via Decentralized Dataset Distillation in Resource-Constrained Edge Environments
Rui Song
Dai Liu
Da Chen
Andreas Festag
Carsten Trinitis
Martin Schulz
Alois C. Knoll
DD
FedML
25
61
0
24 Aug 2022
An Information-Theoretic Justification for Model Pruning
An Information-Theoretic Justification for Model Pruning
Berivan Isik
Tsachy Weissman
Albert No
92
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
183
355
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
174
760
0
28 Sep 2019
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