Results 1 - 10 of 6,548

Weighted low-rank approximations.

by Nathan Srebro , Tommi Jaakkola - 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 low-rank approximation problems, which, unlike their unweighted version, do not admit a closedform solution in general. We analyze ..."
Abstract - Cited by 198 (10 self) - Add to MetaCart
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 low-rank approximation problems, which, unlike their unweighted version, do not admit a closedform solution in general. We

Generalized Low Rank Approximations of Matrices

by Jieping Ye - 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 ..."
Abstract - Cited by 110 (6 self) - Add to MetaCart
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

Low-rank

by Rikard Falkeborn, Johan Löfberg, Anders Hansson
"... exploitation in semidefinite programming for control ..."
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exploitation in semidefinite programming for control

Low-rank

by M. Bebendorf
"... approximation of elliptic boundary value problems with high-contrast coefficients∗ ..."
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approximation of elliptic boundary value problems with high-contrast coefficients∗

The Augmented Lagrange Multiplier Method for Exact Recovery of Corrupted Low-Rank Matrices

by Zhouchen Lin, Minming Chen, Leqin Wu, Yi Ma , 2009
"... ..."
Abstract - Cited by 329 (26 self) - Add to MetaCart
Abstract not found

Weighted Low-Rank Approximations

by Nathan Srebro Nati, Tommi Jaakkola - 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 low-rank approximation problems, which, unlike their unweighted version, do not admit a closedform solution in general. We analyze, in a ..."
Abstract - Cited by 8 (0 self) - Add to MetaCart
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 low-rank approximation problems, which, unlike their unweighted version, do not admit a closedform solution in general. We analyze

Low Rank Circulant Approximation

by Moody T. Chu, Robert J. Plemmons
"... 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 ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
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

by Moody Chu And, Moodyt. Chuandrobertj. Plemmonsy
"... 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

by Jing-rebecca Li, Jacob White - 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 right-hand side −BBT is assume ..."
Abstract - Cited by 106 (4 self) - Add to MetaCart
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 right-hand side −BBT

Structured Low Rank Approximation

by Moody T. Chu , Robert E. Funderlic, Robert J. Plemmons - 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 ..."
Abstract - Cited by 17 (1 self) - Add to MetaCart
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 of 6,548