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» An Overview Of Inverse Problem Regularization Using Sparsity
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TMI
2010
143views more  TMI 2010»
13 years 1 months ago
Data Specific Spatially Varying Regularization for Multimodal Fluorescence Molecular Tomography
Fluorescence molecular tomography (FMT) allows in vivo localization and quantification of fluorescence biodistributions in whole animals. The ill-posed nature of the tomographic re...
Damon Hyde, Eric L. Miller, Dana H. Brooks, Vasili...
ICML
2009
IEEE
13 years 4 months ago
Multiple indefinite kernel learning with mixed norm regularization
We address the problem of learning classifiers using several kernel functions. On the contrary to many contributions in the field of learning from different sources of information...
Matthieu Kowalski, Marie Szafranski, Liva Ralaivol...
TMI
2010
298views more  TMI 2010»
13 years 1 months ago
An Efficient Numerical Method for General Lp Regularization in Fluorescence Molecular Tomography
Abstract--Reconstruction algorithms for fluorescence tomography have to address two crucial issues : (i) the ill-posedness of the reconstruction problem, (ii) the large scale of nu...
Jean-Charles Baritaux, Kai Hassler, Michael Unser
ICASSP
2011
IEEE
12 years 10 months ago
Dual constrained TV-based regularization
Algorithms based on the minimization of the Total Variation are prevalent in computer vision. They are used in a variety of applications such as image denoising, compressive sensi...
Camille Couprie, Hugues Talbot, Jean-Christophe Pe...
ICASSP
2008
IEEE
14 years 1 months ago
Insights into the stable recovery of sparse solutions in overcomplete representations using network information theory
In this paper, we examine the problem of overcomplete representations and provide new insights into the problem of stable recovery of sparse solutions in noisy environments. We es...
Yuzhe Jin, Bhaskar D. Rao