Yingjie Song

FedAlign: Differentially Private Distribution Alignment for Non-IID Federated Learning

Federated Learning (FL) enables collaborative model training without sharing raw data, but client data are often Non-Independent and Identically Distributed (Non-IID), which often slow convergence and degrade global performance. Meanwhile, privacy preservation is also a critical concern in FL. To ad