AsyFed: Accelerated Federated Learning With Asynchronous Communication Mechanism-Reference-Cited by-同舟云学术

AsyFed: Accelerated Federated Learning With Asynchronous Communication Mechanism

Published:2023-05-15 Issue:10 Volume:10 Page:8670-8683
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Li Zhixin¹^ORCID,Huang Chunpu¹,Gai Keke²^ORCID,Lu Zhihui¹^ORCID,Wu Jie¹,Chen Lulu¹^ORCID,Xu Yangchuan¹,Choo Kim-Kwang Raymond³^ORCID

Affiliation:

1. School of Computer Science, Fudan University, Shanghai, China

2. School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, China

3. Department of Information Systems and Cyber Security and Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX, USA

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Shanghai Science and Technology Innovation Action Plan Project

Cloud Technology Endowed Professorship

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/10119650/09999005.pdf?arnumber=9999005

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