Jinlin He

InfRA-FL: Information-Driven Robust Federated Learning via Saturation-Aware Reinforcement Learning

Client selection is a critical mechanism for ensuring robust convergence in Federated Learning (FL) systems, yet it remains vulnerable to Non-IID data distributions and Byzantine attacks. Deep Reinforcement Learning (DRL) has shown promise for automated client selection, yet existing methods suffer from three structura...