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A High-Performance Federated Learning Aggregation Algorithm Based on Learning Rate Adjustment and Client Sampling

Federated learning is a distributed learning framework designed to protect user privacy, widely applied across various domains. However, existing federated learning algorithms face challenges, including slow convergence, significant loss fluctuations during aggregation, and imbalanced client samplin...

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Principais autores: Yulian Gao, Gehao Lu, Jimei Gao, Jinggang Li
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2023-10-01
Serier:Mathematics
Fag:
distributed learning
federated learning
aggregation algorithm
weighted sampling
learning rate adjustment
Online adgang:https://www.mdpi.com/2227-7390/11/20/4344
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