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» An Asymptotic Property of Model Selection Criteria
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TIT
1998
126views more  TIT 1998»
13 years 4 months ago
An Asymptotic Property of Model Selection Criteria
—Probability models are estimated by use of penalized log-likelihood criteria related to AIC and MDL. The accuracies of the density estimators are shown to be related to the trad...
Yuhong Yang, Andrew R. Barron
JMLR
2012
11 years 7 months ago
Factorized Asymptotic Bayesian Inference for Mixture Modeling
This paper proposes a novel Bayesian approximation inference method for mixture modeling. Our key idea is to factorize marginal log-likelihood using a variational distribution ove...
Ryohei Fujimaki, Satoshi Morinaga
ESANN
2006
13 years 6 months ago
Degeneracy in model selection for SVMs with radial Gaussian kernel
We consider the model selection problem for support vector machines applied to binary classification. As the data generating process is unknown, we have to rely on heuristics as mo...
Tobias Glasmachers
TSP
2011
170views more  TSP 2011»
12 years 11 months ago
Model Selection for Sinusoids in Noise: Statistical Analysis and a New Penalty Term
—Detection of the number of sinusoids embedded in noise is a fundamental problem in statistical signal processing. Most parametric methods minimize the sum of a data fit (likeli...
Boaz Nadler, Leonid Kontorovich
ICML
2008
IEEE
14 years 6 months ago
Bolasso: model consistent Lasso estimation through the bootstrap
We consider the least-square linear regression problem with regularization by the 1-norm, a problem usually referred to as the Lasso. In this paper, we present a detailed asymptot...
Francis R. Bach