FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server

Hong Zhang, Ji Liu, Juncheng Jia +3

Despite achieving remarkable performance, Federated Learning (FL) suffers from two critical challenges, i.e., limited computational resources and low training efficiency. In this p…