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» Convex Sparse Matrix Factorizations
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146
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SIAMMAX
2010
224views more  SIAMMAX 2010»
14 years 10 months ago
Robust Approximate Cholesky Factorization of Rank-Structured Symmetric Positive Definite Matrices
Abstract. Given a symmetric positive definite matrix A, we compute a structured approximate Cholesky factorization A RT R up to any desired accuracy, where R is an upper triangula...
Jianlin Xia, Ming Gu
JMLR
2012
13 years 6 months ago
Sparse Higher-Order Principal Components Analysis
Traditional tensor decompositions such as the CANDECOMP / PARAFAC (CP) and Tucker decompositions yield higher-order principal components that have been used to understand tensor d...
Genevera Allen
PPAM
2007
Springer
15 years 10 months ago
A Supernodal Out-of-Core Sparse Gaussian-Elimination Method
Abstract. We present an out-of-core sparse direct solver for unsymmetric linear systems. The solver factors the coefficient matrix A into A = PLU using Gaussian elimination with pa...
Sivan Toledo, Anatoli Uchitel
134
Voted
SDM
2010
SIAM
168views Data Mining» more  SDM 2010»
15 years 2 months ago
Convex Principal Feature Selection
A popular approach for dimensionality reduction and data analysis is principal component analysis (PCA). A limiting factor with PCA is that it does not inform us on which of the o...
Mahdokht Masaeli, Yan Yan, Ying Cui, Glenn Fung, J...
136
Voted
ICIP
2008
IEEE
16 years 5 months ago
Face hallucination VIA sparse coding
In this paper, we address the problem of hallucinating a high resolution face given a low resolution input face. The problem is approached through sparse coding. To exploit the fa...
Jianchao Yang, Hao Tang, Yi Ma, Thomas S. Huang