IEEE

Joint Client and Cross-Client Edge Selection for Cost-Efficient Federated Learning of Graph Convolutional Networks

Abstract: Graph-structured data applications promote the development of Graph Neural Networks (GNN) in recent years. Due to privacy concerns, collecting graph data stored in massive client devices for ...
IEEE

The Diversity Bonus: Learning From Dissimilar Clients in Personalized Federated Learning

Abstract: Personalized federated learning (PFL) allows clients to collaboratively train their personalized models to handle situations where data from different clients are not independent and ...