FedRDS: Federated Learning on Non-IID Data via Regularization and Data Sharing

FedRDS: Federated Learning on Non-IID Data via Regularization and Data Sharing

Federated learning (FL) is an emerging decentralized machine learning framework enabling private global model training by collaboratively leveraging local client data without transferring it centrally. Unlike traditional distributed optimization, FL trains the model at the local client and then aggr...

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Bibliographic Details
Main Authors:	Yankai Lv, Haiyan Ding, Hao Wu, Yiji Zhao, Lei Zhang
Format:	Article
Language:	English
Published:	MDPI AG 2023-12-01
Series:	Applied Sciences
Subjects:	federated learning non-IID data regularization data sharing machine learning
Online Access:	https://www.mdpi.com/2076-3417/13/23/12962

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