搜索结果: 1-12 共查到“管理学 Oracle Inequalities”相关记录12条 . 查询时间(0.14 秒)
Modern statistical estimation via oracle inequalities
Modern statistical estimation oracle inequalities
2015/6/17
A number of fundamental results in modern statistical theory involve thresholding estimators. This survey paper aims at reconstructing the history of how thresholding rules came to be popular in stati...
Anisotropic oracle inequalities in noisy quantization
Quantization Deconvolution Fast rates Margin assumption,k-means clus-tering
2013/6/13
The effect of errors in variables in quantization is investigated. We prove general exact and non-exact oracle inequalities with fast rates for an empirical minimization based on a noisy sample $Z_i=X...
Oracle inequalities for computationally adaptive model selection
Oracle computationally adaptive model selection
2012/9/17
We analyze general model selection procedures using penalized empirical loss minimization under computational constraints. While classical model selection approaches do not consider computational aspe...
Gaussian Oracle Inequalities for Structured Selection in Non-Parametric Cox Model
Gaussian Oracle Inequalities Structured Selection Non-Parametric Cox Model
2012/9/19
To better understand the interplay of censoring and sparsity we develop finite sample properties of nonparametric Cox proportional hazard乫s model. Due to high impact of sequencing data, carrying genet...
The Lasso, correlated design, and improved oracle inequalities
compatibility correlation entropy high-dimensional model
2011/7/19
We study high-dimensional linear models and the $\ell_1$-penalized least squares estimator, also known as the Lasso estimator.
Sharp oracle inequalities and slope heuristic for specification probabilities estimation in general random fields
Sharp oracle inequalities slope heuristic specification probabilities estimation
2011/7/5
We provide new methods for estimation of the one-point specification probabilities in general discrete random fields.
Sharp non-asymptotic oracle inequalities for nonparametric heteroscedastic regression models
Adaptive estimation Heteroscedastic regression Nonasymptoticestimation Nonparametric estimation Oracle inequality
2010/3/10
An adaptive nonparametric estimation procedure is constructed
for heteroscedastic regression when the noise variance depends on the
unknown regression. A non-asymptotic upper bound for a quadratic
...
Sparsity oracle inequalities for the Lasso
sparsity oracle inequalities Lasso penalized least squares dimension reduction aggregation mutual coherence
2009/9/16
This paper studies oracle properties of $ell_1$-penalized least squares in nonparametric regression setting with random design. We show that the penalized least squares estimator satisfies sparsity or...
LASSO, Iterative Feature Selection and the Correlation Selector: Oracle inequalities and numerical performances
Regression estimation statistical learning confidence regions shrinkage and thresholding methods LASSO
2009/9/16
We propose a general family of algorithms for regression estimation with quadratic loss, on the basis of geometrical considerations. These algorithms are able to select relevant functions into a large...
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...
Sparsity oracle inequalities for the Lasso
sparsity oracle inequalities Lasso penalized least squares nonparametric regression dimension reduction
2010/4/29
This paper studies oracle properties of ℓ1-penalized least squares
in nonparametric regression setting with random design. We show that the
penalized least squares estimator satisfies sparsity...
Structural adaptation via LLp-norm oracle inequalities
structural adaptation oracle inequalities minimax risk adaptive estimation optimal rates of convergence
2010/4/28
In this paper we study the problem of adaptive estimation of a multivariate function
satisfying some structural assumption. We propose a novel estimation procedure that
adapts simultaneously to unkn...
