Moxuan Zeng

FedPKDA: Personalized Federated Learning with Privacy-Preserving Knowledge Dynamic Alignment

Personalized Federated Learning (PFL), which aims to customize models for each client while preserving data privacy, has become an important research topic in addressing the challenges of data heterogeneity. Existing studies usually enhance the localization of global parameters by injecting local in