Xian-Chao Zhang

Joint Optimization for Federated Learning and Transmission over Unreliable Wireless Networks with Heterogeneous Data

A federated random walk averaging framework is proposed, which is a variant of federated averaging (FedAvg) that mitigates data heterogeneity by updating models along random walk (RW) paths and aggregating them at the server and reduces the problem to a general form agnostic to task type and model architecture.