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» Sparse Recovery Using Sparse Random Matrices
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CORR
2012
Springer
272views Education» more  CORR 2012»
13 years 5 months ago
Fast and Exact Top-k Search for Random Walk with Restart
Graphs are fundamental data structures and have been employed for centuries to model real-world systems and phenomena. Random walk with restart (RWR) provides a good proximity sco...
Yasuhiro Fujiwara, Makoto Nakatsuji, Makoto Onizuk...
TIT
2010
112views Education» more  TIT 2010»
14 years 4 months ago
Exponential bounds implying construction of compressed sensing matrices, error-correcting codes, and neighborly polytopes by ran
In [12] the authors proved an asymptotic sampling theorem for sparse signals, showing that n random measurements permit to reconstruct an N-vector having k nonzeros provided n >...
David L. Donoho, Jared Tanner
TSP
2008
151views more  TSP 2008»
14 years 9 months ago
Reduce and Boost: Recovering Arbitrary Sets of Jointly Sparse Vectors
The rapid developing area of compressed sensing suggests that a sparse vector lying in a high dimensional space can be accurately and efficiently recovered from only a small set of...
Moshe Mishali, Yonina C. Eldar
COCO
2011
Springer
217views Algorithms» more  COCO 2011»
13 years 9 months ago
Noisy Interpolation of Sparse Polynomials, and Applications
Let f ∈ Fq[x] be a polynomial of degree d ≤ q/2. It is well-known that f can be uniquely recovered from its values at some 2d points even after some small fraction of the valu...
Shubhangi Saraf, Sergey Yekhanin
ICASSP
2011
IEEE
14 years 1 months ago
Denoising of image patches via sparse representations with learned statistical dependencies
We address the problem of denoising for image patches. The approach taken is based on Bayesian modeling of sparse representations, which takes into account dependencies between th...
Tomer Faktor, Yonina C. Eldar, Michael Elad