1 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.LG2020★ 1 cited
Distributed Bayesian Matrix Decomposition for Big Data Mining and Clustering
Chihao Zhang, Yang Yang, Wei Zhang +1
Matrix decomposition is one of the fundamental tools to discover knowledge from big data generated by modern applications. However, it is still inefficient or infeasible to process…
cs.LG2019
Matrix Normal PCA for Interpretable Dimension Reduction and Graphical Noise Modeling
Chihao Zhang, Kuo Gai, Shihua Zhang
Principal component analysis (PCA) is one of the most widely used dimension reduction and multivariate statistical techniques. From a probabilistic perspective, PCA seeks a low-dim…
cs.CV2017★ 1 cited
Bayesian Joint Matrix Decomposition for Data Integration with Heterogeneous Noise
Chihao Zhang, Shihua Zhang
Matrix decomposition is a popular and fundamental approach in machine learning and data mining. It has been successfully applied into various fields. Most matrix decomposition meth…