Fair Wireless Federated Learning Through the Identification of a Common Descent Direction-Reference-Cited by-同舟云学术

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Fair Wireless Federated Learning Through the Identification of a Common Descent Direction

Published:2024-03 Issue:3 Volume:28 Page:567-571
ISSN:1089-7798
Container-title:IEEE Communications Letters
language:
Short-container-title:IEEE Commun. Lett.

Author:

Mohajer Hamidi Shayan¹^ORCID,Damen Oussama¹^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/4234/10466646/10381881.pdf?arnumber=10381881

Reference20 articles.

1. Communication-efficient learning of networks from decentralized data;McMahan

2. Edge Learning for B5G Networks With Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing

3. Federated Learning for Wireless Communications: Motivation, Opportunities, and Challenges

4. Fair resource allocation in federated learning;Li

5. Tilted empirical risk minimization;Li

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Trustworthy Federated Learning: A Comprehensive Review, Architecture, Key Challenges, and Future Research Prospects;IEEE Open Journal of the Communications Society;2024

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