4 citations · 5 across the 7 of their papers we have counts for
12 papers
Distributed Learning for Principle Eigenspaces without Moment Constraints
Yong He, Zichen Liu, Yalin Wang
Distributed Principal Component Analysis (PCA) has been studied to deal with the case when data are stored across multiple machines and communication cost or privacy concerns prohi…
Manifold Principle Component Analysis for Large-Dimensional Matrix Elliptical Factor Model
ZeYu Li, Yong He, Xinbing Kong +1
Matrix factor model has been growing popular in scientific fields such as econometrics, which serves as a two-way dimension reduction tool for matrix sequences. In this article, we…
Simultaneous Cluster Structure Learning and Estimation of Heterogeneous Graphs for Matrix-variate fMRI Data
Dong Liu, Changwei Zhao, Yong He +3
Graphical models play an important role in neuroscience studies, particularly in brain connectivity analysis. Typically, observations/samples are from several heterogenous groups a…
Joint Learning of Multiple Differential Networks with fMRI data for Brain Connectivity Alteration Detection
Hao Chen, Ying Guo, Yong He +3
In this study we focus on the problem of joint learning of multiple differential networks with function Magnetic Resonance Imaging (fMRI) data sets from multiple research centers.…
Simultaneous Differential Network Analysis and Classification for High-dimensional Matrix-variate Data, with application to Brain Connectivity Alteration Detection and fMRI-guided Medical Diagnoses of Alzheimer's Disease
Chen Hao, Guo Ying, He Yong +6
Alzheimer's disease (AD) is the most common form of dementia, which causes problems with memory, thinking and behavior. Growing evidence has shown that the brain connectivity netwo…
Robust Covariance Estimation for High-dimensional Compositional Data with Application to Microbial Communities Analysis
Yong He, Pengfei Liu, Xinsheng Zhang +1
Microbial communities analysis is drawing growing attention due to the rapid development of high-throughput sequencing techniques nowadays. The observed data has the following typi…