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Variable Selection with Exponential Weights and $l_0$-Penalization
Variable selection model selection sparse linear model xponential weights Gibbs sampler identifiability condition.
2012/9/17
In the context of a linear model with a sparse coefficient vector, exponential weights methods have been shown to be achieve oracle inequalities for prediction. We show that such methods also succeed ...
Consistent selection of tuning parameters via variable selection stability
kappa coefficient penalized regression selection consistency stability tuning
2012/9/17
Penalized regression models are popularly used in high-dimensional data analysis to conduct variable selection and model fitting simultaneously. Whereas success has been widely reported in literature,...
Honest variable selection in linear and logistic regression models via $ell_1$ and $ell_1 + ell_2$ penalization
penalty sparse consistent variable selection regression generalized linear models logistic regression
2009/9/16
This paper investigates correct variable selection in finite samples via $ell_1$ and $ell_1 + ell_2$ type penalization schemes. The asymptotic consistency of variable selection immediately follows fro...
Variable selection for multicategory SVM via adaptive sup-norm regularization
Classification L1-norm penalty multicategory sup-norm SVM
2009/9/16
Support Vector Machine (SVM) is a popular classification paradigm in machine learning and has achieved great success in real applications. However, the standard SVM can not select variables automatica...
Structured variable selection in support vector machines
Classification Heredity Nonparametric estimation Support vector machine Variable selection
2009/9/16
When applying the support vector machine (SVM) to high-dimensional classification problems, we often impose a sparse structure in the SVM to eliminate the influences of the irrelevant predictors. The ...
Admissible, consistent multiple testing with applications including variable selection
backward method exponential family forward method step-down procedures step-up procedures
2009/9/16
For multivariate normal models and some exponential family models a multiple testing stepwise method is offered that is both admissible and consistent. The method is readily adaptable to selecting var...