Taming Staleness in Asynchronous Federated Learning With System Heterogeneity
Asynchronous federated learning is a distributed machine learning framework designed for parallel and distributed systems. However, system heterogeneity in communication and computation can cause stragglers to upload stale updates, which may degrade the performance of the global model. Existing studies primarily focus...