2024
Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability
NeurIPS 2024poster
Addressing intermittent client availability is critical for the real-world deployment of federated learning algorithms. Most prior work either overlooks the potential non-stationarity in the dynamics of client unavailability or requires substantial memory/computation overhead. We study federated lea…