84 search results - page 2 / 17 » Gradient-Based Methods for Sparse Recovery |
147
Voted
TSP
2010
14 years 7 months ago
2010
We present two simple methods for recovering sparse signals from a series of noisy observations. The theory of compressed sensing (CS) requires solving a convex constrained minimiz...
143
Voted
SIAMIS
2011
14 years 8 months ago
2011
Abstract. Accurate signal recovery or image reconstruction from indirect and possibly undersampled data is a topic of considerable interest; for example, the literature in the rece...
113
Voted
ICASSP
2011
IEEE
14 years 4 months ago
2011
IEEE
The 2- 1 sparse signal minimization problem can be solved efficiently by gradient projection. In many applications, the signal to be estimated is known to lie in some range of va...
138
Voted
JMLR
2006
15 years 1 months ago
2006
Many kernel learning algorithms, including support vector machines, result in a kernel machine, such as a kernel classifier, whose key component is a weight vector in a feature sp...
123
Voted
ICA
2007
Springer
15 years 2 months ago
2007
Springer
Abstract. This paper introduces gradient based method for robust assessment of the sparse pulse sources, such as motor unit innervation pulse trains in the filed of electromyograp...