… Personalization methods in federated learning aim to balance the benefits of federated and
local training for data availability, communication cost, and robustness to client heterogeneity…

… named pFedPT, a personalized federated learning method based on visual prompts. We
make the first attempt to introduce visual prompts to personalized federated learning, using a …

… personalized perspective. Motivated by the fact that, in practice, the participation of clients in
federation … propose a new framework for personalized federated learning. In the proposed …

… personalized federated learning framework, dubbed CGPFL, to handle the challenge of
statistical heterogeneity (Non-IID) in the federated … personalized federated learning and further …

… To this end, we introduce a new subgraph FL problem, personalized … than learning a single
global model, and propose a novel framework, FEDerated Personalized sUBgraph learning (…

… personalization method to address the statistical heterogeneity issue … Federated Learning.
Flow is motivated by the observation that the personalized models from existing personalized …

… Federated learning [1, 2] is a popular distributed learning framework developed for edge …
rounds, personalization, lack of labels, robustness, and continuation in federated learning are …

… the relationship between consumer electronics with personalized recommendation systems
(PRS) and how federated learning can enhance the security and privacy challenges in PRS …

… of low rank matrix for federated learning [20]. Right illustrates our factorization method for
agnostic personalized federated learning, which utilizes rank 1 vectors and highly sparse bias. …

… participating in federated training has been proposed and widely studied. In this paper, we
propose a personalized federated learning algorithm that can provide a personalized local …