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We present a new computational approach to approximating a large, noisy data table by a low-rank matrix with sparse singular vectors.
Cross-validatory estimation of the number of components in factor and principal component models
S. Wold · 1978
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A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis
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Online Learning for Matrix Factorization and Sparse Coding
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Reconstruction of a low-rank matrix in the presence of gaussian noise
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PMA: Penalized Multivariate Analysis , 2010
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A generalized least squares matrix decomposition
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On consistency and sparsity for principal components analysis in high dimensions
I. M. Johnstone and A. Y. Lu · 2009
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Discussion of “On consistency and sparsity for principal components analysis in high dimensions” by Johnstone and Lu
B. Nadler · 2009
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Bi-cross-validation of the SVD and the nonnegative matrix factorization
A. B. Owen and P. O. Perry · 2009
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Biclustering via sparse singular value decomposition
M. Lee, H. Shen, J. Z. Huang, and J. S. Marron
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