52 search results - page 3 / 11 » Bayesian Compressive Sensing Using Laplace Priors |
ECML
2007
Springer
13 years 11 months ago
2007
Springer
We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The paramete...
TSP
2010
12 years 12 months ago
2010
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...
CORR
2008
Springer
13 years 5 months ago
2008
Springer
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...
ICASSP
2010
IEEE
13 years 3 months ago
2010
IEEE
In this paper, we introduce a novel bayesian compressive sensing (CS) technique for phonetic classification. CS is often used to characterize a signal from a few support training...
TSP
2008
13 years 5 months ago
2008
The data of interest are assumed to be represented as N-dimensional real vectors, and these vectors are compressible in some linear basis B, implying that the signal can be recons...