26 search results - page 1 / 6 » RLS-weighted Lasso for adaptive estimation of sparse signals |
ICASSP
2009
IEEE
13 years 11 months ago
2009
IEEE
The batch least-absolute shrinkage and selection operator (Lasso) has well-documented merits for estimating sparse signals of interest emerging in various applications, where obse...
NIPS
1998
13 years 6 months ago
1998
Adaptive Ridge is a special form of Ridge regression, balancing the quadratic penalization on each parameter of the model. It was shown to be equivalent to Lasso (least absolute s...
TSP
2010
12 years 11 months ago
2010
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
ICASSP
2010
IEEE
13 years 5 months ago
2010
IEEE
The least-absolute shrinkage and selection operator (Lasso) is a popular tool for joint estimation and continuous variable selection, especially well-suited for the under-determin...
SDM
2012
SIAM
11 years 7 months ago
2012
SIAM
In this paper, we consider the multi-task sparse learning problem under the assumption that the dimensionality diverges with the sample size. The traditional l1/l2 multi-task lass...