3 papers
cs.LG2026
Personalized Federated Hierarchical Gaussian Processes for Privacy-Preserving Modeling of Heterogeneous Distributed Systems
Xianjian Xie, Hao Yan
We present Personalized Federated Hierarchical Gaussian Processes (pFedHGP) for probabilistic regression and classification when data are distributed across heterogeneous clients.…
stat.AP2025
MOOSE ProbML: Parallelized Probabilistic Machine Learning and Uncertainty Quantification for Computational Energy Applications
Somayajulu L. N. Dhulipala, Peter German, Yifeng Che +5
This paper presents the development and demonstration of massively parallel probabilistic machine learning (ML) and uncertainty quantification (UQ) capabilities within the Multiphy…
cs.LG2023
Adversarial Client Detection via Non-parametric Subspace Monitoring in the Internet of Federated Things
Xianjian Xie, Xiaochen Xian, Dan Li +1
The Internet of Federated Things (IoFT) represents a network of interconnected systems with federated learning as the backbone, facilitating collaborative knowledge acquisition whi…