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Breaking the Prototype Bias Loop: Confidence-Aware Federated Contrastive Learning for Highly Imbalanced Clients

Fuente: arXiv

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Dettagli Bibliografici
Autori principali:	Wu, Tian-Shuang, Lyu, Shen-Huan, Chen, Ning, He, Yi-Xiao, Tang, Bing, Ye, Baoliu, Zhang, Qingfu
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning Distributed, Parallel, and Cluster Computing
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

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