搜索结果: 16-30 共查到“管理学 Model Selection”相关记录46条 . 查询时间(0.319 秒)
Consistency of Bayesian Linear Model Selection With a Growing Number of Parameters
Bayesian model selection growing number of parameters Posterior model consistency consistency of Bayes factor consistency of posterior odds ratio Gibbs sampling
2011/3/18
Linear models with a growing number of parameters have been widely used in modern statistics. One important problem about this kind of model is the variable selection issue. Bayesian approaches, which...
The goal of cross-domain object matching (CDOM) is to find correspondence between two sets of objects in different domains in an unsupervised way. Photo album summarization is a typical application of...
Model Selection by Loss Rank for Classification and Unsupervised Learning
Classification graphical models loss rank principle model selection
2010/11/9
Hutter (2007) recently introduced the loss rank principle (LoRP) as a general-purpose principle for model selection. The LoRP enjoys many attractive prop-erties and deserves further investigations. Th...
Error Prediction and Model Selection via Unbalanced Expander Graphs
Error Prediction Model Selection Unbalanced Expander Graphs
2010/10/19
We investigate deterministic design matrices for the fundamental problems of error prediction and model selection. Our deterministic design matrices are constructed from unbalanced expander graphs, a...
Stochastic model selection for Mixtures of Matrix-Normals
Mixture models birth and death process Gibbs sampler
2010/10/19
Finite mixtures of matrix normal distributions are a powerful tool for classifying three-way data in unsupervised problems. The distribution of each component is assumed to be a matrix variate normal ...
High-dimensional Ising model selection using ${\ell_1}$-regularized logistic regression
High-dimensional model selection
2010/10/14
We consider the problem of estimating the graph associated with a binary Ising Markov random field. We describe a method based on $\ell_1$-regularized logistic regression, in which the neighborhood of...
A model selection approach to genome wide association studies
Genome wide association Multiple testing Linear regression,
2010/10/14
For the vast majority of genome wide association studies (GWAS) published so far, statistical analysis was performed by testing markers individually. In this article we present some elementary statis...
Adaptive estimation of linear functionals by model selection
Nonparametric regression white noise model adaptive estimation model selection pointwise adaptive estimation
2009/9/16
We propose an estimation procedure for linear functionals based on Gaussian model selection techniques. We show that the procedure is adaptive, and we give a non asymptotic oracle inequality for the r...
Estimation of Gaussian graphs by model selection
Gaussian graphical model Random matrices Model selection Penalized empirical risk
2009/9/16
We investigate in this paper the estimation of Gaussian graphs by model selection from a non-asymptotic point of view. We start from a $n$-sample of a Gaussian law $mathbb{P}_C$ in $mathbb{R}^p$ and f...
Nonparametric Bayesian model selection and averaging
Adaptation rate of convergence Bayes factor rate of contraction
2009/9/16
We consider nonparametric Bayesian estimation of a probability density p based on a random sample of size n from this density using a hierarchical prior. The prior consists, for instance, of prior wei...
Model selection by resampling penalization
Non-parametric statistics resampling exchangeable weighted bootstrap model selection penalization non-parametric regression
2009/9/16
In this paper, a new family of resampling-based penalization procedures for model selection is defined in a general framework. It generalizes several methods, including Efron's bootstrap penalization ...
Thresholding-based iterative selection procedures for model selection and shrinkage
Sparsity nonconvex penalties thresholding model selection & shrinkage lasso ridge SCAD
2009/9/16
This paper discusses a class of thresholding-based iterative selection procedures (TISP) for model selection and shrinkage. People have long before noticed the weakness of the convex $l_1$-constraint ...
General oracle inequalities for model selection
general oracle inequalities model selection
2009/9/16
Model selection is often performed by empirical risk minimization. The quality of selection in a given situation can be assessed by risk bounds, which require assumptions both on the margin and the ta...
High-dimensional Gaussian model selection on a Gaussian design
High-dimensional Gaussian model selection Gaussian design
2010/4/30
High-dimensional Gaussian model selection on a Gaussian design。
Gaussian model selection with an unknown variance
Model selection penalized criterion AIC FPE BIC AMDL variable selection change-points detection adaptive estimation
2010/4/26
Let Y be a Gaussian vector whose components are independent
with a common unknown variance. We consider the problem of estimating
the mean μ of Y by model selection. More precisely, we start
with a...