Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients

no code implementations • NeurIPS 2021 • Aritra Mitra, Rayana Jaafar, George J. Pappas, Hamed Hassani

We consider a standard federated learning (FL) architecture where a group of clients periodically coordinate with a central server to train a statistical model.

Federated Learning