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CORR
2010
Springer
130views Education» more  CORR 2010»
13 years 5 months ago
Phase Transitions for Greedy Sparse Approximation Algorithms
A major enterprise in compressed sensing and sparse approximation is the design and analysis of computationally tractable algorithms for recovering sparse, exact or approximate, s...
Jeffrey D. Blanchard, Coralia Cartis, Jared Tanner...
SIAMREV
2010
174views more  SIAMREV 2010»
13 years 10 hour ago
Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
The affine rank minimization problem consists of finding a matrix of minimum rank that satisfies a given system of linear equality constraints. Such problems have appeared in the ...
Benjamin Recht, Maryam Fazel, Pablo A. Parrilo
CORR
2010
Springer
115views Education» more  CORR 2010»
13 years 3 months ago
Tight oracle bounds for low-rank matrix recovery from a minimal number of random measurements
This paper presents several novel theoretical results regarding the recovery of a low-rank matrix from just a few measurements consisting of linear combinations of the matrix entr...
Emmanuel J. Candès, Yaniv Plan
CORR
2010
Springer
94views Education» more  CORR 2010»
13 years 2 months ago
Segmented compressed sampling for analog-to-information conversion: Method and performance analysis
A new segmented compressed sampling (CS) method for analog-to-information conversion (AIC) is proposed. An analog signal measured by a number of parallel branches of mixers and int...
Omid Taheri, Sergiy A. Vorobyov
KDD
2009
ACM
188views Data Mining» more  KDD 2009»
14 years 5 months ago
Mining discrete patterns via binary matrix factorization
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
Bao-Hong Shen, Shuiwang Ji, Jieping Ye