89 search results - page 14 / 18 » Sparse Recovery by Non-convex Optimization -- Instance Optim... |
CORR
2011
Springer
12 years 11 months ago
2011
Springer
—This paper addresses the problem of simultaneous signal recovery and dictionary learning based on compressive measurements. Multiple signals are analyzed jointly, with multiple ...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We consider the problem of learning a sparse multi-task regression, where the structure in the outputs can be represented as a tree with leaf nodes as outputs and internal nodes a...
CORR
2010
Springer
13 years 4 months ago
2010
Springer
Abstract. In this paper, we show how to efficiently and effectively extract a rich class of low-rank textures in a 3D scene from 2D images despite significant distortion and warpin...
ECCV
2008
Springer
14 years 9 months ago
2008
Springer
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
CIMAGING
2009
13 years 8 months ago
2009
The Dantzig selector is a near ideal estimator for recovery of sparse signals from linear measurements in the presence of noise. It is a convex optimization problem which can be r...