A Knowledge-Imparting Generative Modelling Framework for Heterogeneous Federated Learning
Federated learning aims to provide security for client data privacy in practical machine learning applications. In principle, a global server aggregates the models produced by local clients to obtain a global model. However, the server is challenged when collaborating with local clients handling non-identically distrib...