DA-PFL: Dynamic Affinity Aggregation for Personalized Federated Learning

arXiv:2403.09284v1 Announce Type: new
Abstract: Personalized federated learning becomes a hot research topic that can learn a personalized learning model for each client. Existing personalized federated learning models prefer to aggregate similar clients with similar data distribution to improve the performance of learning models. However, similaritybased personalized federated learning methods may exacerbate the class imbalanced problem. In this paper, we propose a novel Dynamic Affinity-based Personalized Federated Learning model (DA-PFL) to alleviate the class imbalanced problem during federated learning. Specifically, …

abstract aggregation arxiv client cs.dc cs.lg data distribution dynamic federated learning hot however learn performance personalized research type