A Multi-agent Reinforcement Learning Approach for Efficient Client Selection in Federated Learning

Sai Qian Zhang, Jieyu Lin, Qi Zhang

Federated learning (FL) is a training technique that enables client devices to jointly learn a shared model by aggregating locally-computed models without exposing their raw data.…