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Weighted lowrank approximations.
 In Int. Conf. Machine Learning (ICML),
, 2003
"... Abstract We study the common problem of approximating a target matrix with a matrix of lower rank. We provide a simple and efficient (EM) algorithm for solving weighted lowrank approximation problems, which, unlike their unweighted version, do not admit a closedform solution in general. We analyze ..."
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Cited by 198 (10 self)
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Abstract We study the common problem of approximating a target matrix with a matrix of lower rank. We provide a simple and efficient (EM) algorithm for solving weighted lowrank approximation problems, which, unlike their unweighted version, do not admit a closedform solution in general. We
Generalized Low Rank Approximations of Matrices
 MACHINE LEARNING
, 2004
"... We consider the problem of computing low rank approximations of matrices. The novelty of our approach is that the low rank approximations are on a sequence of matrices. Unlike the ..."
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Cited by 110 (6 self)
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We consider the problem of computing low rank approximations of matrices. The novelty of our approach is that the low rank approximations are on a sequence of matrices. Unlike the
Lowrank
"... approximation of elliptic boundary value problems with highcontrast coefficients∗ ..."
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approximation of elliptic boundary value problems with highcontrast coefficients∗
The Augmented Lagrange Multiplier Method for Exact Recovery of Corrupted LowRank Matrices
, 2009
"... ..."
Weighted LowRank Approximations
 In 20th International Conference on Machine Learning
, 2003
"... We study the common problem of approximating a target matrix with a matrix of lower rank. We provide a simple and e#cient (EM) algorithm for solving weighted lowrank approximation problems, which, unlike their unweighted version, do not admit a closedform solution in general. We analyze, in a ..."
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Cited by 8 (0 self)
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We study the common problem of approximating a target matrix with a matrix of lower rank. We provide a simple and e#cient (EM) algorithm for solving weighted lowrank approximation problems, which, unlike their unweighted version, do not admit a closedform solution in general. We analyze
Low Rank Circulant Approximation
"... Partially due to the fact that the empirical data collected in practice by devices with finite bandwidth often neither maintain the specified structure nor induce a certain desired rank, structured low rank approximation arises in many important applications. Approximation by structured low rank mat ..."
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Cited by 1 (0 self)
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Partially due to the fact that the empirical data collected in practice by devices with finite bandwidth often neither maintain the specified structure nor induce a certain desired rank, structured low rank approximation arises in many important applications. Approximation by structured low rank
Low Rank Circulant Approximation
"... Partially due to the fact that the empirical data collected in practice by devices with finite bandwidth often neither maintain the specified structure nor induce a certain desired rank, structured low rank approximation arises in many important applications. Approximation by structured low rank mat ..."
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Partially due to the fact that the empirical data collected in practice by devices with finite bandwidth often neither maintain the specified structure nor induce a certain desired rank, structured low rank approximation arises in many important applications. Approximation by structured low rank
Low rank solutions of Lyapunov equations
 SIAM Journal Matrix Anal. Appl
, 2002
"... Abstract. This paper presents the Cholesky factor–alternating direction implicit (CF–ADI) algorithm, which generates a low rank approximation to the solution X of the Lyapunov equation AX +XAT = −BBT. The coefficient matrix A is assumed to be large, and the rank of the righthand side −BBT is assume ..."
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Cited by 106 (4 self)
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Abstract. This paper presents the Cholesky factor–alternating direction implicit (CF–ADI) algorithm, which generates a low rank approximation to the solution X of the Lyapunov equation AX +XAT = −BBT. The coefficient matrix A is assumed to be large, and the rank of the righthand side −BBT
Structured Low Rank Approximation
 LINEAR ALGEBRA APPL
, 2002
"... This paper concerns the construction of a structured low rank matrix that is nearest to a given matrix. The notion of structured low rank approximation arises in various applications, ranging from signal enhancement to protein folding to computer algebra, where the empirical data collected in a matr ..."
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Cited by 17 (1 self)
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This paper concerns the construction of a structured low rank matrix that is nearest to a given matrix. The notion of structured low rank approximation arises in various applications, ranging from signal enhancement to protein folding to computer algebra, where the empirical data collected in a
Results 1  10
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