On Model Transmission Strategies in Federated Learning With Lossy Communications-Reference-Cited by-同舟云学术

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On Model Transmission Strategies in Federated Learning With Lossy Communications

Published:2023 Issue: Volume: Page:1-14
ISSN:1045-9219
Container-title:IEEE Transactions on Parallel and Distributed Systems
language:
Short-container-title:IEEE Trans. Parallel Distrib. Syst.

Author:

Su Xiaoxin¹^ORCID,Zhou Yipeng²^ORCID,Cui Laizhong³^ORCID,Liu Jiangchuan⁴^ORCID

Affiliation:

1. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China

2. School of Computing, FSE, Macquarie University, NSW, Australia

3. College of Computer Science and Software Engineering

4. School of Computing Science, Simon Fraser University, Burnaby, BC, Canada

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Hardware and Architecture,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/71/4359390/10032555.pdf?arnumber=10032555

Reference57 articles.

1. Gradient sparsification for communication-efficient distributed optimization;wangni;Proc Adv Neural Inf Process Syst,2018

2. Federated Learning over Wireless Networks: Optimization Model Design and Analysis

3. Modeling TCP throughput

4. Optimal Rate Adaption in Federated Learning with Compressed Communications

5. Learning multiple layers of features from tiny images;krizhevsky,2009

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