Heterogeneity-Guided Client Sampling: Towards Fast and Efficient Non-IID Federated Learning

This has motivated numerous studies aiming to reduce the variance and improve convergence of FL on non-IID data [6, 9, 14, 17, 19, 30]. On another note, constraints on communication resources and therefore on the number of clients that may participate in training additionally complicate implementation of FL schemes.