搜索结果: 16-25 共查到“理学 LASSO”相关记录25条 . 查询时间(0.143 秒)
We also
study a condition under which the coefficient paths of the lasso are monotone, and hence the different algorithms coincide. Finally, we compare the
lasso and forward stagewise pro...
Proximal methods for the latent group lasso penalty
Structured sparsity proximal methods regularization
2012/11/23
We consider a regularized least squares problem, with regularization by structured sparsity-inducing norms, which extend the usual $\ell_1$ and the group lasso penalty, by allowing the subsets to over...
Non-asymptotic Oracle Inequalities for the Lasso and Group Lasso in high dimensional logistic model
Logistic model Lasso Group Lasso High-dimensional
2012/6/19
We consider the problem of estimating a function $f_{0}$ in logistic regression model. We propose to estimate this function $f_{0}$ by a sparse approximation build as a linear combinaison of elements ...
The lasso is a popular tool for sparse linear regression, especially for problems in which the number of variables p exceeds the number of observations n. But when p>n, the lasso criterion is not stri...
Model selection by LASSO methods in a change-point model
LASSO change-points selection criterion asymptotic behavior oracle properties
2011/8/25
Abstract: The paper considers a linear regression model with multiple change-points occurring at unknown times. The LASSO technique is very interesting since it allows the parametric estimation, inclu...
LASSO Methods for Gaussian Instrumental Variables Models
LASSO Methods Gaussian Instrumental Variables Models
2011/3/2
In this note, we propose the use of sparse methods (e.g. LASSO, Post-LASSO,p LASSO, and Post-
p LASSO) to form rst-stage predictions and estimate optimal instru-ments in linear instrumental variable...
Strong rules for discarding predictors in lasso-type problems
discarding predictors lasso-type problems
2010/11/15
We consider rules for discarding predictors in lasso regression and related problems, for computational efficiency. El Ghaoui et al (2010) propose "SAFE" rules that guarantee that a coefficient will ...
A local stochastic Lipschitz condition with application to Lasso for high dimensional generalized linear models
Lasso sparsity measure concentration generalized linear models
2010/11/30
For regularized estimation, the upper tail behavior of the random Lipschitz coefficient asso-
ciated with empirical loss functions is known to play an important role in the error bound of
Lasso for ...
Square-Root Lasso: Pivotal Recovery of Sparse Signals via Conic Programming
High-dimensional sparse model unknown sigma conic programming
2010/12/16
We propose a pivotal method for estimating high-dimensional sparse linear re-gression models, where the overall number of regressors p is large, possibly much larger than n, but only s regressors are ...
本文提出一种新的分层混合模糊-神经网络(HHFNN)算法.在模糊系统中使用Takagi-Sugeno模型和三角波隶属函数.同时,为降低离散输入变量中可能存在的强交互作用,采用了系数收缩机制中的Lasso函数.最后,以福建的漳平洛阳—安溪潘田地区LANDSAT ETM+遥感影像数据地物分类为例,应用本文的改进算法与其他神经网络算法进行分析比较,得到了较高的分类精度,验证了采用基于Lasso函数的T-...