FedEve: On Bridging the Client Drift and Period Drift for Cross-device Federated Learning

Tao Shen, Zexi Li, Didi Zhu +3

Federated learning (FL) is a machine learning paradigm that allows multiple clients to collaboratively train a shared model without exposing their private data. Data heterogeneity…