Chao Huo

FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update

As a promising approach to deal with distributed data, Federated Learning (FL) achieves major advancements in recent years. FL enables collaborative model training by exploiting the raw data dispersed in multiple edge devices. However, the data is generally non-independent and identically distribute…