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» Estimating random variables from random sparse observations
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TSP
2008
106views more  TSP 2008»
13 years 7 months ago
Identification of Matrices Having a Sparse Representation
We consider the problem of recovering a matrix from its action on a known vector in the setting where the matrix can be represented efficiently in a known matrix dictionary. Conne...
Götz E. Pfander, Holger Rauhut, Jared Tanner
CISS
2010
IEEE
12 years 11 months ago
Turbo reconstruction of structured sparse signals
—This paper considers the reconstruction of structured-sparse signals from noisy linear observations. In particular, the support of the signal coefficients is parameterized by h...
Philip Schniter
CVPR
2008
IEEE
14 years 9 months ago
Selective hidden random fields: Exploiting domain-specific saliency for event classification
Classifying an event captured in an image is useful for understanding the contents of the image. The captured event provides context to refine models for the presence and appearan...
Vidit Jain, Amit Singhal, Jiebo Luo
APPROX
2004
Springer
135views Algorithms» more  APPROX 2004»
14 years 27 days ago
The Diameter of Randomly Perturbed Digraphs and Some Applications.
The central observation of this paper is that if ǫn random arcs are added to any n-node strongly connected digraph with bounded degree then the resulting graph has diameter O(ln ...
Abraham Flaxman, Alan M. Frieze
CVPR
2011
IEEE
13 years 2 months ago
Accelerated Low-Rank Visual Recovery by Random Projection
Exact recovery from contaminated visual data plays an important role in various tasks. By assuming the observed data matrix as the addition of a low-rank matrix and a sparse matri...
Yadong Mu, Jian Dong, Xiaotong Yuan, Shuicheng Yan