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» Sparse Recovery Using Sparse Random Matrices
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CORR
2011
Springer
168views Education» more  CORR 2011»
14 years 4 months ago
Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection
We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can ...
Abhimanyu Das, David Kempe
CRV
2004
IEEE
226views Robotics» more  CRV 2004»
15 years 1 months ago
Inter-Image Statistics for Scene Reconstruction
We present an approach for inferring complete depth maps from intensity images and sparse depth information. This paper developed prior work which incrementally completes a sparse...
Luz Abril Torres-Méndez, Gregory Dudek, Pau...
ISCAS
2007
IEEE
126views Hardware» more  ISCAS 2007»
15 years 4 months ago
Theory and Implementation of an Analog-to-Information Converter using Random Demodulation
— The new theory of compressive sensing enables direct analog-to-information conversion of compressible signals at subNyquist acquisition rates. We develop new theory, algorithms...
Jason N. Laska, Sami Kirolos, Marco F. Duarte, Tam...
IJON
2010
181views more  IJON 2010»
14 years 8 months ago
Active learning with extremely sparse labeled examples
An active learner usually assumes there are some labeled data available based on which a moderate classifier is learned and then examines unlabeled data to manually label the mos...
Shiliang Sun, David R. Hardoon
ISSAC
2007
Springer
106views Mathematics» more  ISSAC 2007»
15 years 4 months ago
Numerical techniques for computing the inertia of products of matrices of rational numbers
Consider a rational matrix, particularly one whose entries have large numerators and denominators, but which is presented as a product of very sparse matrices with relatively smal...
John P. May, B. David Saunders, David Harlan Wood