Federated learning (FL) enables multiple clients to train a model while keeping their data
private collaboratively. Previous studies have shown that data heterogeneity between clients …

Federated Learning (FL) allows training machine learning models in privacy-constrained
scenarios by enabling the cooperation of edge devices without requiring local data sharing …

This paper investigates resource allocation to provide heterogeneous users with customized
virtual reality (VR) services in a mobile edge computing (MEC) system. We first introduce a …

Federated learning (FL) allows multiple clients to train a global model while keeping data
locally. It has been well recognized that FL suffers from data heterogeneity, leading to drifts …