Zifeng Xu

MSCFL: Model Structure-Aware Clustered Federated Learning for System Heterogeneity and Data Drift

Federated Learning (FL) faces significant challenges arising from both data and system heterogeneity. While Clustered Federated Learning (CFL) mitigates data heterogeneity by grouping clients with similar data distributions, it remains vulnerable to system heterogeneity, which can slow convergence d