1 citations · 1 across the 4 of their papers we have counts for
4 papers
Non-segmental Bayesian Detection of Multiple Change-points
Chong Zhong, Zhihua Ma, Xu Zhang +1
We propose an original and general NOn-SEgmental (NOSE) approach for the detection of multiple change-points. NOSE identifies change-points by the non-negligibility of posterior es…
Modeling and Learning on High-Dimensional Matrix-Variate Sequences
Xu Zhang, Catherine C. Liu, Jianhua Guo +2
We propose a new matrix factor model, named RaDFaM, which is strictly derived based on the general rank decomposition and assumes a structure of a high-dimensional vector factor mo…
Tucker tensor factor models: matricization and mode-wise PCA estimation
Xu Zhang, Guodong Li, Catherine C. Liu +1
High-dimensional, higher-order tensor data are gaining prominence in a variety of fields, including but not limited to computer vision and network analysis. Tensor factor models, i…
Low-rank Latent Matrix-factor Prediction Modeling for Generalized High-dimensional Matrix-variate Regression
Yuzhe Zhang, Xu Zhang, Hong Zhang +2
Motivated by diagnosing the COVID-19 disease using 2D image biomarkers from computed tomography (CT) scans, we propose a novel latent matrix-factor regression model to predict resp…