47 search results - page 2 / 10 » A Regularization Approach to Nonlinear Variable Selection |
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Voted
ESANN
2008
14 years 11 months ago
2008
Our goal is proposing an unbiased framework for gene expression analysis based on variable selection combined with a significance assessment step. We start by discussing the need ...
ICDM
2007
IEEE
14 years 11 months ago
2007
IEEE
An easily implementable mixed-integer algorithm is proposed that generates a nonlinear kernel support vector machine (SVM) classifier with reduced input space features. A single ...
CORR
2007
Springer
14 years 9 months ago
2007
Springer
The large number of spectral variables in most data sets encountered in spectral chemometrics often renders the prediction of a dependent variable uneasy. The number of variables ...
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
This paper addresses the problem of active model selection for nonlinear dynamical systems. We propose a novel learning approach that selects the most informative subset of time-d...
AAAI
2007
14 years 12 months ago
2007
Sparsity-promoting L1-regularization has recently been succesfully used to learn the structure of undirected graphical models. In this paper, we apply this technique to learn the ...