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» Bayesian compressive sensing and projection optimization
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ICML
2007
IEEE
11 years 19 days ago
Bayesian compressive sensing and projection optimization
This paper introduces a new problem for which machine-learning tools may make an impact. The problem considered is termed "compressive sensing", in which a real signal o...
Shihao Ji, Lawrence Carin
CORR
2008
Springer
234views Education» more  CORR 2008»
9 years 12 months ago
Bayesian Compressive Sensing via Belief Propagation
Compressive sensing (CS) is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable, sub-N...
Dror Baron, Shriram Sarvotham, Richard G. Baraniuk
ICIP
2009
IEEE
9 years 9 months ago
Informative sensing of natural images
The theory of compressed sensing tells a dramatic story that sparse signals can be reconstructed near-perfectly from a small number of random measurements. However, recent work ha...
Hyun Sung Chang, Yair Weiss, William T. Freeman
ACISICIS
2008
IEEE
10 years 1 months ago
Efficient Projection for Compressed Sensing
Compressed sensing (CS), a joint compression and sensing process, is a emerging field of activity in which the signal is sampled and simultaneously compressed at a greatly reduced...
Vo Dinh Minh Nhat, Duc Vo, Subhash Challa, Sungyou...
TSP
2010
9 years 6 months ago
Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds
Nonparametric Bayesian methods are employed to constitute a mixture of low-rank Gaussians, for data x RN that are of high dimension N but are constrained to reside in a low-dimen...
Minhua Chen, Jorge Silva, John William Paisley, Ch...
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