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Graph realization and lowrank . . .
, 2012
"... This thesis consists of five chapters, and focuses on two main problems: the graph realization problem with its applications to localization of sensor network and structural biology, and the lowrank matrix completion problem. Chapter 1 is a brief introduction to rigidity theory and supplies the bac ..."
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This thesis consists of five chapters, and focuses on two main problems: the graph realization problem with its applications to localization of sensor network and structural biology, and the lowrank matrix completion problem. Chapter 1 is a brief introduction to rigidity theory and supplies
Upgrading of LowRank Coals
, 1997
"... The names PDF ™ , CDL ™ , and SynCoal ® are registered trademarks for the upgraded fuels discussed in this document. PDF and CDL are registered trademarks of the ENCOAL Corporation, and SynCoal is a registered trademark of the Rosebud SynCoal Partnership. These marks are so identified when the produ ..."
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the products are identified initially, but for readability, the trademark symbols are not repeated throughout the report. Upgrading of LowRank Coals Cover images: (upper left) The ENCOAL demonstration site near Gillette, Wyoming, and (lower right)
Accelerated lowrank visual recovery by random projection
 in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR
"... Exact recovery from contaminated visual data plays an important role in various tasks. By assuming the observed data matrix as the addition of a lowrank matrix and a sparse matrix, theoretic guarantee exists under mild conditions for exact data recovery. Practically matrix nuclear norm is adopted ..."
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Cited by 13 (0 self)
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Exact recovery from contaminated visual data plays an important role in various tasks. By assuming the observed data matrix as the addition of a lowrank matrix and a sparse matrix, theoretic guarantee exists under mild conditions for exact data recovery. Practically matrix nuclear norm is adopted
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 7 (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
Generalized LowRank Approximations
"... We study the frequent 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 simple matrix factorization problems, do not admit a closed form solution in general. W ..."
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We study the frequent 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 simple matrix factorization problems, do not admit a closed form solution in general
Generalized LowRank Approximations
, 2003
"... We study the frequent 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 simple matrix factorization problems, do not admit a closed form solution in general. We ..."
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We study the frequent 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 simple matrix factorization problems, do not admit a closed form solution in general
The Augmented Lagrange Multiplier Method for Exact Recovery of Corrupted LowRank Matrices
, 2009
"... ..."
Multidimensional Signal Processing for Sparse and LowRank Problems
, 2014
"... Sparse models have attracted great attention from the research community due to their ..."
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Sparse models have attracted great attention from the research community due to their
Sparse and LowRank Matrix Decompositions
, 2009
"... Suppose we are given a matrix that is formed by adding an unknown sparse matrix to an unknown lowrank matrix. Our goal is to decompose the given matrix into its sparse and lowrank components. Such a problem arises in a number of applications in model and system identification, but obtaining an ex ..."
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Cited by 31 (2 self)
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Suppose we are given a matrix that is formed by adding an unknown sparse matrix to an unknown lowrank matrix. Our goal is to decompose the given matrix into its sparse and lowrank components. Such a problem arises in a number of applications in model and system identification, but obtaining
APPROXIMATE RANKDETECTING FACTORIZATION OF LOWRANK TENSORS
"... We present an algorithm, AROFAC2, which detects the (CP)rank of a degree 3 tensor and calculates its factorization into rankone components. We provide generative conditions for the algorithm to work and demonstrate on both synthetic and real world data that AROFAC2 is a potentially outperforming ..."
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We present an algorithm, AROFAC2, which detects the (CP)rank of a degree 3 tensor and calculates its factorization into rankone components. We provide generative conditions for the algorithm to work and demonstrate on both synthetic and real world data that AROFAC2 is a potentially outperforming
Results 1  10
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479,280