Stochastic Client Selection for Federated Learning With Volatile Clients-Reference-Cited by-同舟云学术

Stochastic Client Selection for Federated Learning With Volatile Clients

Author:

Huang Tiansheng¹^ORCID,Lin Weiwei¹^ORCID,Shen Li²^ORCID,Li Keqin³^ORCID,Zomaya Albert Y.⁴^ORCID

Affiliation:

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

2. JD Explore Academy, JD.com, Beijing, China

3. Department of Computer Science, State University of New York, New Paltz, NY, USA

4. School of Computer Science, The University of Sydney, Sydney, NSW, Australia

Funder

Key-Area Research and Development Program of Guangdong Province

National Natural Science Foundation of China

Guangzhou Science and Technology Program Key Projects

Guangzhou Development Zone Science and Technology

Guangdong Marine Economic Development Special Fund Project

Science and Technology Innovation 2030—“Brain Science and Brain-Like Research” Major Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

Link

Reference29 articles.

1. Communication-efficient on-device machine learning: Federated distillation and augmentation under non-IID private data;jeong;arXiv 1811 11479,2018

2. Federated optimization in heterogeneous networks;li;arXiv 1812 06127,2018

3. Towards flexible device participation in federated learning;ruan;Proc Int Conf Artif Intell Stat,2021

5. Energy-efficient radio resource allocation for federated edge learning;zeng;arXiv 1907 06040,2019

Cited by 56 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