Federated Learning Meets Multi-Objective Optimization
Federated Learning Meets Multi-Objective Optimization
Federated learning has emerged as a promising, massively distributed way to train a joint deep model over large amounts of edgedevices while keeping private user data strictly on device. In this work, motivated from ensuring fairness among users and robustness against malicious adversaries, we formulate federated learning as multi-objective optimization …