IEEE

Federated Reinforcement Learning for Energy-Efficient D2D-IoT Networks With AoI Awareness

Abstract: This paper proposes a federated reinforcement learning (FRL) framework for optimizing energy efficiency (EE) and Age of Information (AoI) in device-to-device (D2D) and Internet of Things ...
IEEE

Communication-Efficient Federated Learning for Edge Computing With Gradient Leakage Defense

Abstract: Federated learning (FL) has emerged as a promising paradigm for privacy-preserving model training across distributed edge devices, enabling local data utilization without explicit sharing.