Federated Learning Based Fault Diagnosis Driven by Intra-Client Imbalance Degree

Federated learning is an effective means to combine model information from different clients to achieve joint optimization when the model of a single client is insufficient. In the case when there is an inter-client data imbalance, it is significant to design an imbalanced federation aggregation str...

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Bibliografiske detaljer

Principais autores:	Funa Zhou, Yi Yang, Chaoge Wang, Xiong Hu
Format:	Artigo
Sprog:	Inglês
Udgivet:	MDPI AG 2023-04-01
Serier:	Entropy
Fag:	fault diagnosis federated learning imbalance mode mismatch intra-client imbalance degree joint optimization
Online adgang:	https://www.mdpi.com/1099-4300/25/4/606
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