… Personalized federated learning (PFL) has been widely … the generic global and personalized
local models are captured by … architecture into generic versus personalized components, or …

… personalized federated learning (GPFL), which considers both generalization and personalization
to … , but it mainly resorts to the model personalization for the unseen clients by test-time …

… (2) how important personalization truly is for realistic federated applications. To better …
personalized federated learning. Motley consists of a suite of cross-device and cross-silo federated …

… personalized federated learning method for ECG classification. We explore feature alignment
for personalization … dataset, it shows that personalization benefits the local model with high …

… Our main contributions are summarized as follows: • We focus on personalized federated
learning, highlighting two factors of inconsistency evident both at the intraclient and inter-client …

… In this paper, we addressed the problem of personalized federated learning under different
types of heterogeneity, including label distribution skew as well as label concept drift and …

Federated Learning (FL) has recently attracted great interest in sensor-based human activity
recognition (HAR) tasks. However, in real-world environment, sensor data on devices is non…

Federated learning (FL) enables distributed mobile devices to collaboratively learn a shared
… In this paper, we propose TailorFL, a dual-personalized FL framework, which tailors a …

… Personalized Federated Learning faces many challenges such as expensive com… local
models to achieve personalization. We follow the avenue and propose a personalized FL method …

… of federated learning [30,36,37,45], which aims to train a global machine learning model on
a … Focusing on the personalized federated learning setting, we adopt the notation of [27] to …