CosPer: An adaptive personalized approach for enhancing fairness and robustness of federated learning
P Ren, K Qi, J Li, T Yan, Q Dai - Information Sciences, 2024 - Elsevier
Federated learning (FL) enables clients to collaboratively train a global model while
safeguarding the privacy of their respective data. In practical applications, the data …
safeguarding the privacy of their respective data. In practical applications, the data …
[HTML][HTML] A personalized federated learning method based on the residual multi-head attention mechanism
Z Li, Z Zhong, P Zuo, H Zhao - Journal of King Saud University-Computer …, 2024 - Elsevier
Federated Learning (FL) is a distributed machine learning technique for training machine
learning models across multiple clients collaboratively. It allows multiple local devices to …
learning models across multiple clients collaboratively. It allows multiple local devices to …
Federated Learning for Vehicle Trajectory Prediction: Methodology and Benchmark Study
Vehicle Trajectory Prediction (VTP) plays a pivotal role in the Internet of Vehicles (IoV),
significantly aiding in motion planning and accident prevention. Nonetheless, the field faces …
significantly aiding in motion planning and accident prevention. Nonetheless, the field faces …
Regularizing and Aggregating Clients with Class Distribution for Personalized Federated Learning
G Lee, D Choi - arXiv preprint arXiv:2406.07800, 2024 - arxiv.org
Personalized federated learning (PFL) enables customized models for clients with varying
data distributions. However, existing PFL methods often incur high computational and …
data distributions. However, existing PFL methods often incur high computational and …