Gradient Scheduling With Global Momentum for Asynchronous Federated Learning in Edge Environment-Reference-Cited by-同舟云学术

Gradient Scheduling With Global Momentum for Asynchronous Federated Learning in Edge Environment

Author:

Wang Haozhao¹^ORCID,Li Ruixuan¹^ORCID,Li Chengjie¹,Zhou Pan²^ORCID,Li Yuhua¹^ORCID,Xu Wenchao³^ORCID,Guo Song³^ORCID

Affiliation:

1. School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China

2. School of Cyber Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China

3. Department of Computing, The Hong Kong Polytechnic University, Hong Kong

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Research Grants Council of the Hong Kong Special Administrative Region, China

Hong Kong RGC Research Impact Fund

General Research Fund

Shenzhen Science and Technology Innovation Commission

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

Link

Reference49 articles.

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4. Large scale distributed deep networks;dean;Proc 26th Annu Conf Neural Inf Process Syst,2012

5. Deep gradient compression: Reducing the communication bandwidth for distributed training;lin;arXiv 1712 01887,2017

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