FedGAMMA: Federated Learning With Global Sharpness-Aware Minimization-Reference-Cited by-同舟云学术

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FedGAMMA: Federated Learning With Global Sharpness-Aware Minimization

Published:2024 Issue: Volume: Page:1-14
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Dai Rong¹^ORCID,Yang Xun¹^ORCID,Sun Yan²,Shen Li³^ORCID,Tian Xinmei¹^ORCID,Wang Meng⁴^ORCID,Zhang Yongdong¹^ORCID

Affiliation:

1. School of Information Science and Technology, University of Science and Technology of China, Hefei, China

2. School of Computer Science, University of Sydney, Sydney, NSW, Australia

3. JD Explore Academy, Beijing, China

4. School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/10269141.pdf?arnumber=10269141

Cited by 2 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. Generalized Federated Learning via Gradient Norm-Aware Minimization and Control Variables;Mathematics;2024-08-26

2. Multicenter Hierarchical Federated Learning With Fault-Tolerance Mechanisms for Resilient Edge Computing Networks;IEEE Transactions on Neural Networks and Learning Systems;2024

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