AAAI
2011
13 years 17 days ago
2011
Variable selection problems are typically addressed under a penalized optimization framework. Nonconvex penalties such as the minimax concave plus (MCP) and smoothly clipped absol...
JMLR
2010
13 years 7 months ago
2010
We propose a novel application of the Simultaneous Orthogonal Matching Pursuit (SOMP) procedure to perform variable selection in ultra-high dimensional multiple output regression ...
EVOW
2009
Springer
13 years 10 months ago
2009
Springer
Abstract. Evolutionary algorithms such as genetic programming and grammatical evolution have been used for simultaneously optimizing network architecture, variable selection, and w...
MA
2010
Springer
13 years 11 months ago
2010
Springer
: Semiparametric linear transformation models have received much attention due to its high flexibility in modeling survival data. A useful estimating equation procedure was recent...
IJDAR
2010
13 years 11 months ago
2010
Inthispaper,weproposeadescriptorcombination method, which enables to improve significantly the recognition rate compared to the recognition rates obtained by each descriptor. This ...
CP
2010
Springer
13 years 11 months ago
2010
Springer
Generic SAT solvers have been very successful in solving hard combinatorial problems in various application areas, including AI planning. There is potential for improved performanc...
SCFBM
2008
14 years 20 hour ago
2008
The main problem in any model-building situation is to choose from a large set of covariates those that should be included in the "best" model. A decision to keep a vari...
MP
2007
14 years 1 days ago
2007
The selection of the branching variable can greatly affect the speed of the branch and bound solution of a mixed-integer or integer linear program. Traditional approaches to branc...
CSDA
2004
14 years 12 days ago
2004
Variable selection consists in identifying a k-subset of a set of original variables that is optimal for a given criterion of adequate approximation to the whole data set. Several...
BMCBI
2007
14 years 17 days ago
2007
Variable importance measures for random forests have been receiving increased attention as a means of variable selection in many classification tasks in bioinformatics and relate...