2 papers
cs.LG2025
pFedWN: A Personalized Federated Learning Framework for D2D Wireless Networks with Heterogeneous Data
Zhou Ni, Masoud Ghazikor, Morteza Hashemi
Traditional Federated Learning (FL) approaches often struggle with data heterogeneity across clients, leading to suboptimal model performance for individual clients. To address thi…
cs.LG2023
Efficient Cluster Selection for Personalized Federated Learning: A Multi-Armed Bandit Approach
Zhou Ni, Morteza Hashemi
Federated learning (FL) offers a decentralized training approach for machine learning models, prioritizing data privacy. However, the inherent heterogeneity in FL networks, arising…