Clustered Federated Learning Based on Momentum Gradient Descent for Heterogeneous Data
Data heterogeneity may significantly deteriorate the performance of federated learning since the client’s data distribution is divergent. To mitigate this issue, an effective method is to partition these clients into suitable clusters. However, existing clustered federated learning is only based on...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI
2023
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| Subjects: | |
| Online Access: | View Fulltext in Publisher View in Scopus |