Zhenshen Liu

FedCDWA: Decoupled Federated Prototype Distillation with Hierarchical Wasserstein Aggregation

Federated learning enables decentralized clients to collaboratively train models without sharing local data. However, heterogeneous client distributions often induce client drift and hinder convergence. This paper proposes FedCDWA, a decoupled hierarchical federated distillation framework. FedCDWA d…