4 Papers
6 Citations
Wei Hu is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Nonparametric statistics & Matrix (mathematics). The author has an hindex of 3, co-authored 4 publications.
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Papers
Matrix Linear Discriminant Analysis.
TL;DR: A novel linear discriminant analysis approach for the classification of high-dimensional matrix-valued data that commonly arises from imaging studies is proposed using an efficient nuclear norm penalized regression that encourages a low-rank structure.
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Nonparametric matrix response regression with application to brain imaging data analysis.
TL;DR: A novel nonparametric matrix response regression model is proposed to characterize the nonlinear association between 2D image outcomes and predictors such as time and patient information and shows that the method outperforms other existing approaches in simulations.
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Nonparametric Matrix Response Regression with Application to Brain Imaging Data Analysis
TL;DR: In this paper, a nonparametric matrix response regression model is proposed to characterize the nonlinear association between 2D image outcomes and predictors such as time and patient information, which can capture the underlying low-rank structure of the dynamic 2D images.
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•Posted Content
Matrix Linear Discriminant Analysis
TL;DR: In this article, a linear discriminant analysis approach was proposed for the classification of high-dimensional matrix-valued data that commonly arises from imaging studies, motivated by the equivalence of the conventional Linear Discriminant Analysis and the ordinary least squares, and an efficient nuclear norm penalized regression that encourages a low-rank structure.