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» Bayesian compressive sensing and projection optimization
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ICML
2007
IEEE
15 years 10 months 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»
14 years 9 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
14 years 7 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
14 years 11 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
14 years 4 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...