Efficient Federated Learning Using Dynamic Update and Adaptive Pruning with Momentum on Shared Server Data

Ji Liu, Juncheng Jia, Hong Zhang +5

Despite achieving remarkable performance, Federated Learning (FL) encounters two important problems, i.e., low training efficiency and limited computational resources. In this pape…