Zhenyan Liu

Classifier Clustering and Feature Alignment for Federated Learning under Distributed Concept Drift

Data heterogeneity is one of the key challenges in federated learning, and many efforts have been devoted to tackling this problem. However, distributed concept drift with data heterogeneity, where clients may additionally experience different concept drifts, is a largely unexplored area. In this wo…