ISFL: Federated Learning for Non-i.i.d. Data with Local Importance Sampling

Zheqi Zhu, Yuchen Shi, Pingyi Fan +2

As a promising learning paradigm integrating computation and communication, federated learning (FL) proceeds the local training and the periodic sharing from distributed clients. D…