Akihiro Toyoda

Single-Round Clustered Federated Learning via Data Collaboration Analysis for Non-IID Data

Federated Learning (FL) enables distributed learning across multiple clients without sharing raw data. When statistical heterogeneity across clients is severe, Clustered Federated Learning (CFL) can improve performance by grouping similar clients and training cluster-wise models. However, most CFL a