2 papers
cs.LG2025
Bridging Generalization Gap of Heterogeneous Federated Clients Using Generative Models
Ziru Niu, Hai Dong, A. K. Qin
Federated Learning (FL) is a privacy-preserving machine learning framework facilitating collaborative training across distributed clients. However, its performance is often comprom…
cs.LG2024
FedSPU: Personalized Federated Learning for Resource-constrained Devices with Stochastic Parameter Update
Ziru Niu, Hai Dong, A. K. Qin
Personalized Federated Learning (PFL) is widely employed in IoT applications to handle high-volume, non-iid client data while ensuring data privacy. However, heterogeneous edge dev…