104 search results - page 2 / 21 » An Overview Of Inverse Problem Regularization Using Sparsity |
ECCV
2008
Springer
15 years 11 months ago
2008
Springer
This article proposes a new framework to regularize linear inverse problems using the total variation on non-local graphs. This nonlocal graph allows to adapt the penalization to t...
NIPS
2004
14 years 11 months ago
2004
Many works have shown that strong connections relate learning from examples to regularization techniques for ill-posed inverse problems. Nevertheless by now there was no formal ev...
PKDD
2010
Springer
14 years 8 months ago
2010
Springer
In this paper, we introduce a simple but efficient greedy algorithm, called SINCO, for the Sparse INverse COvariance selection problem, which is equivalent to learning a sparse Ga...
63
Voted
SIAMSC
2008
14 years 9 months ago
2008
Abstract. A new iterative algorithm for the solution of minimization problems in infinitedimensional Hilbert spaces which involve sparsity constraints in form of p-penalties is pro...
81
Voted
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
This paper investigates a new learning formulation called structured sparsity, which is a naturalextensionofthestandardsparsityconceptinstatisticallearningandcompressivesensing. B...