7 citations · 11 across the 4 of their papers we have counts for
5 papers
Privacy-Preserving Transfer Learning for Community Detection using Locally Distributed Multiple Networks
Xiao Guo, Xuming He, Xiangyu Chang +1
Modern applications increasingly involve highly sensitive network data, where raw edges cannot be shared due to privacy constraints. We propose \texttt{TransNet}, a new spectral cl…
Randomized Spectral Clustering for Large-Scale Multi-Layer Networks
Wenqing Su, Xiao Guo, Xiangyu Chang +1
Large-scale multi-layer networks with large numbers of nodes, edges, and layers arise across various domains, which poses a great computational challenge for the downstream analysi…
Spectral co-Clustering in Multi-layer Directed Networks
Wenqing Su, Xiao Guo, Xiangyu Chang +1
Modern network analysis often involves multi-layer network data in which the nodes are aligned, and the edges on each layer represent one of the multiple relations among the nodes.…
Learning Personalized Brain Functional Connectivity of MDD Patients from Multiple Sites via Federated Bayesian Networks
Shuai Liu, Xiao Guo, Shun Qi +2
Identifying functional connectivity biomarkers of major depressive disorder (MDD) patients is essential to advance understanding of the disorder mechanisms and early intervention.…
Learning Multitask Gaussian Bayesian Networks
Shuai Liu, Yixuan Qiu, Baojuan Li +2
Major depressive disorder (MDD) requires study of brain functional connectivity alterations for patients, which can be uncovered by resting-state functional magnetic resonance imag…