Data Distribution-Aware Online Client Selection Algorithm for Federated Learning in Heterogeneous Networks-Reference-Cited by-同舟云学术

Data Distribution-Aware Online Client Selection Algorithm for Federated Learning in Heterogeneous Networks

Author:

Lee Jaewook¹^ORCID,Ko Haneul²^ORCID,Seo Sangwon³^ORCID,Pack Sangheon³^ORCID

Affiliation:

1. Electronics and Telecommunications Research Institute, Daejeon, South Korea

2. Department of Electronic Engineering, Kyung Hee University, Yongin-si, Gyeonggi-do, South Korea

3. School of Electrical Engineering, Korea University, Seoul, South Korea

Funder

National Research Foundation of Korea

Korean Government

Institute of Information and Communications Technology Planning and Evaluation

Korea government

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering

Link

Reference35 articles.

2. Very deep convolutional networks for large-scale image recognition;simonyan;Proc Int Conf Learn Representations,0

3. Learning multiple layers of features from tiny images;krizhevsky,2009

4. Using confidence bounds for exploitation-exploration trade-offs;auer;J Mach Learn Res,2003

5. Overfitting and underfitting with machine learning algorithms,2016

Cited by 12 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

3. Pre-Training Model and Client Selection Optimization for Improving Federated Learning Efficiency;2024 9th International Conference on Electronic Technology and Information Science (ICETIS);2024-05-17