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Multivariate statistics / Data analysis / Singular value decomposition / Matrix theory / Principal component analysis / Eigenvalues and eigenvectors / Covariance matrix / Variance / Matrix / Algebra / Statistics / Linear algebra


Accepted by Journal of Multivariate Analysis Sparse Principal Component Analysis via Regularized Low Rank Matrix Approximation Haipeng Shen∗and Jianhua Z. Huang† June 7, 2007
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Document Date: 2007-08-08 12:13:02

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File Size: 275,80 KB

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College Station / /

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Texas A&M University / University of North Carolina / Chapel Hill / /

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statistical applications / above algorithm / dimension reduction tool / medical imaging / iterative algorithm / sPCA-rSVD algorithm / /

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Chapel Hill / /

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Department of Statistics and Operations Research / Texas A&M University / University of North Carolina / Department of Statistics / /

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Zamir / Gabriel / /

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Texas / North Carolina / /

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above algorithm / iterative algorithm / simulation / 1 sPCA-rSVD Algorithm / sPCA-rSVD algorithm / DNA Chip / gene expression / medical imaging / /

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