Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning

Zhenheng Tang, Yonggang Zhang, Shaohuai Shi +3

In federated learning (FL), model performance typically suffers from client drift induced by data heterogeneity, and mainstream works focus on correcting client drift. We propose a…