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FedRFQ: Prototype-Based Federated Learning with Reduced Redundancy, Minimal Failure, and Enhanced Quality

Fuente: arXiv

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Dettagli Bibliografici
Autori principali:	Yan, Biwei, Zhang, Hongliang, Xu, Minghui, Yu, Dongxiao, Cheng, Xiuzhen
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Distributed, Parallel, and Cluster Computing Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

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