Cheng Dai

FedCM: Client Clustering and Migration in Federated Learning via Gradient Path Similarity and Update Direction Deviation

Federated learning (FL) enables collaborative training among multiple clients while preserving data privacy. However, its practical application is significantly limited by two major challenges: statistical heterogeneity and data distribution drift. Statistical heterogeneity causes the direction of l