84 search results - page 14 / 17 » Gradient-Based Methods for Sparse Recovery |
ICML
2010
IEEE
13 years 9 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...
ECCV
2008
Springer
14 years 10 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...
ML
2002
ACM
13 years 8 months ago
2002
ACM
We examine linear program (LP) approaches to boosting and demonstrate their efficient solution using LPBoost, a column generation based simplex method. We formulate the problem as...
CORR
2010
Springer
13 years 9 months ago
2010
Springer
Finding the sparsest solution for an under-determined linear system of equations D = s is of interest in many applications. This problem is known to be NP-hard. Recent work studie...
ICIP
2008
IEEE
14 years 3 months ago
2008
IEEE
Compressed sensing(CS) suggests that a signal, sparse in some basis, can be recovered from a small number of random projections. In this paper, we apply the CS theory on sparse ba...