FedCLCC: A personalized federated learning algorithm for edge cloud collaboration based on contrastive learning and conditional computing

FedCLCC: A personalized federated learning algorithm for edge cloud collaboration based on contrastive learning and conditional computing

Federated learning (FL) is a distributed machine learning paradigm for edge cloud computing. FL can facilitate data-driven decision-making in tactical scenarios, effectively addressing both data volume and infrastructure challenges in edge environments. However, the diversity of clients in edge clou...

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Bibliographic Details
Main Authors:	Kangning Yin, Xinhui Ji, Yan Wang, Zhiguo Wang
Format:	Article
Language:	English
Published:	KeAi Communications Co., Ltd. 2025-01-01
Series:	Defence Technology
Subjects:	Federated learning Statistical heterogeneity Personalized model Conditional computing Contrastive learning
Online Access:	http://www.sciencedirect.com/science/article/pii/S2214914724002009
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