PA-CFL: Privacy-Preserving Adaptive Clustered Federated Learning Under Heterogeneous Data
Clustered federated learning (CFL) addresses data heterogeneity by grouping clients with similar data distributions and training personalized models for each cluster. However, existing CFL schemes depend on clustering-related parameters that require prior knowledge of client data distributions. Such information is ofte...