5 search results - page 1 / 1 » Relaxed Lasso |
CSDA
2007
13 years 4 months ago
2007
The Lasso is an attractive regularisation method for high dimensional regression. It combines variable selection with an efficient computational procedure. However, the rate of co...
CHI
2008
ACM
14 years 5 months ago
2008
ACM
Selection is a fundamental task in interactive applications, typically performed by clicking or lassoing items of interest. However, users may require more nuanced forms of select...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
Nonparametric methods are widely applicable to statistical learning problems, since they rely on a few modeling assumptions. In this context, the fresh look advocated here permeat...
JMLR
2010
12 years 11 months ago
2010
Methods based on 1-relaxation, such as basis pursuit and the Lasso, are very popular for sparse regression in high dimensions. The conditions for success of these methods are now ...
JMLR
2012
11 years 7 months ago
2012
Variable selection is an important and practical problem that arises in analysis of many high-dimensional datasets. Convex optimization procedures that arise from relaxing the NP-...