Time-Sensitive Federated Learning With Heterogeneous Training Intensity: A Deep Reinforcement Learning Approach-Reference-Cited by-同舟云学术

Time-Sensitive Federated Learning With Heterogeneous Training Intensity: A Deep Reinforcement Learning Approach

Published:2024-04 Issue:2 Volume:8 Page:1402-1415
ISSN:2471-285X
Container-title:IEEE Transactions on Emerging Topics in Computational Intelligence
language:
Short-container-title:IEEE Trans. Emerg. Top. Comput. Intell.

Author:

Pan Weijian¹^ORCID,Wang Xiumin¹^ORCID,Zhou Pan²^ORCID,Lin Weiwei¹^ORCID

Affiliation:

1. School of Computer Science and Engineering, South China University of Technology, Guangzhou, China

2. Hubei Key Laboratory of Distributed System Security, Hubei Engineering Research Center on Big Data Security, School of Cyber Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China

Funder

National Natural Science Foundation of China

Basic and Applied Basic Research Foundation of Guangdong Province

Major Key Project of PCL

Guangzhou Development Zone Science and Technology Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7433297/10480102/10384474.pdf?arnumber=10384474

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