Client Selection in Federated Learning under Imperfections in Environment

Federated learning promises an elegant solution for learning global models across distributed and privacy-protected datasets. However, challenges related to skewed data distribution, limited computational and communication resources, data poisoning, and free riding clients affect the performance of...

Full description

Bibliographic Details

Published in:	AI
Main Authors:	Sumit Rai, Arti Kumari, Dilip K. Prasad
Format:	Article
Language:	English
Published:	MDPI AG 2022-02-01
Subjects:	federated learning client selection class imbalance free-riders active learning faster convergence
Online Access:	https://www.mdpi.com/2673-2688/3/1/8