管理学 >>> 统计学 >>> 理论统计学 >>> 统计调查分析理论 统计核算理论 统计监督理论 统计预测理论 统计逻辑学 理论统计学其他学科
搜索结果: 1-15 共查到理论统计学 lasso相关记录22条 . 查询时间(0.046 秒)
We study the property of the Fused Lasso Signal Approximator(FLSA) for estimating a blocky signal sequence with additive noise.We transform the FLSA to an ordinary Lasso problem. By studying the prope...
A SPARSE-GROUP LASSO     penalize  regularize  regression  model  nesterov       2015/8/21
For high dimensional supervised learning problems, often using problem specific assumptions can lead to greater accuracy. For problems with grouped covariates, which are believed to have sparse effect...
We introduce a method for learning pairwise interactions in a linear regression or logistic regression model in a manner that satisfies strong hierarchy: whenever an interaction is estimated to be non...
In this paper we consider solving \emph{noisy} under-determined systems of linear equations with sparse solutions. A noiseless equivalent attracted enormous attention in recent years, above all, due t...
The Lasso is a popular statistical tool invented by Robert Tibshirani for linear regression when the number of covariates is greater than or comparable to the number of observations. The validity of t...
We consider a high-dimensional regression model with a possible change-point due to a covariate threshold and develop the Lasso estimator of regression coefficients as well as the threshold parameter....
We study high-dimensional linear models and the $\ell_1$-penalized least squares estimator, also known as the Lasso estimator.
In a nonparametric linear regression model we study a variant of LASSO, called pLASSO, which does not require the knowledge of the scaling parameter σ of the noise or bounds for it. This work derive...
The LASSO is a variable subset selection procedure in statistical linear regression based on ℓ1 penalization of the least-squares operator. Its behavior crucially depends, both in practice and...
In this note, we propose to use sparse methods (e.g. LASSO, Post-LASSO, sqrt-LASSO, and Post-sqrt-LASSO) to form first-stage predictions and estimate optimal instruments in linear instrumental variabl...
The performance of the Lasso is well understood under the assumptions of the standard linear model with homoscedastic noise. However, in several appli-cations, the standard model does not describe the...
The group lasso is a penalized regression method, used in regression problems where the covariates are partitioned into groups to promote sparsity at the group level. Existing methods for finding the ...
We revisit the adaptive Lasso in a high-dimensional linear model, and provide bounds for its prediction error and for its number of false positive selections. We compare the adaptive Lasso with an “...
Given n noisy samples with p dimensions, where n  p, we show that the multi-step thresholding procedure based on the Lasso – we call it the Thresholded Lasso, can accurately estimate a sparse vector ...
The LASSO is a widely used statistical methodology for simultaneous estimation and variable selection. In the last years, many authors analyzed this technique from a theoretical and applied point of...

中国研究生教育排行榜-

正在加载...

中国学术期刊排行榜-

正在加载...

世界大学科研机构排行榜-

正在加载...

中国大学排行榜-

正在加载...

人 物-

正在加载...

课 件-

正在加载...

视听资料-

正在加载...

研招资料 -

正在加载...

知识要闻-

正在加载...

国际动态-

正在加载...

会议中心-

正在加载...

学术指南-

正在加载...

学术站点-

正在加载...