FedMoE: Data-Level Personalization with Mixture of Experts for
Model-Heterogeneous Personalized Federated Learning
FedMoE: Data-Level Personalization with Mixture of Experts for
Model-Heterogeneous Personalized Federated Learning
Federated learning (FL) is widely employed for collaborative training on decentralized data but faces challenges like data, system, and model heterogeneity. This prompted the emergency of model-heterogeneous personalized federated learning (MHPFL). However, concerns persist regarding data and model privacy, model performance, communication, and computational costs in current MHPFL methods. To …