搜索结果: 1-15 共查到“Lasso”相关记录50条 . 查询时间(0.065 秒)
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：A LASSO-based Detection and Identification Method on Actuator Integrity Attacks in Remote Control Systems
LASSO 远程控制系统 执行器 完整性 攻击检测 识别方法
2023/4/28
We consider actuator attacks in a remote control system. Compared with sensor attacks that have been studied in most existing literature, the malicious attacks over actuators can cause more disastrous...
Motivation: Differential network inference is a fundamental and challenging problem to reveal gene interactions and regulation relationships under different conditions. Many algorithms have been devel...
建立住院患者医院下呼吸道感染预测模型，构建新的、简单的风险评分方法。方法 以2014年多家医院感染调查数据为训练集，建立住院患者医院下呼吸道感染的Lasso-logistic回归预测模型，选择贝叶斯信息准则（BIC）最小模型为最终模型，将回归系数放大相同倍数建立评分方法，以2015、2016年调查数据为验证集，并与文献建立的风险评分方法进行比较。
基于Post-LASSO方法的就医需求多控制变量选择
就医 工具变量 交互要素 最小绝对收缩和选择算子(LASSO)
2018/11/15
分析省级层面就医需求的政策变量和交互要素，并控制地区和时间效应的异质性，为精确估计医疗改革效应和医疗机构区域合理布局提供科学依据.以就医需求和就医供给的代理变量、区域特征控制变量建立指标体系，采用Post-double-selection-LASSO方法选择潜在变量及其函数形式.一阶差分、全控制变量和各省标准差集聚三个模型的比较结果显示，标准差集聚模型较好地控制时间趋势和初始差异，证实复杂就医需求...
On Pattern Recovery of The Fused Lasso
Confidence interval jackknife empirical likelihood risk measure
2016/1/25
Quantifying risks is of importance in insurance. In this paper, we employ the jackknife empirical likelihood method to construct confidence intervals for some risk measures and related quantities stud...
Vanilla Lasso for sparse classification under single index models
Vanilla Lasso sparse classification single index models
2016/1/20
This paper study sparse classification problems. We show that under single-index models, vanilla Lasso could give good estimate of unknown parameters. With this result, we see that even if the model i...
On Pattern Recovery of The Fused Lasso
Fused Lasso Non-asymptotic Pattern recovery Preconditioning
2016/1/20
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...
The Lasso under Poisson-like Heteroscedasticity
Lasso Poisson-like Model Sign Consistency Heteroscedas- ticity
2016/1/19
The performance of the Lasso is well understood under the assumptions of the standard sparse linear model with homoscedastic noise. However, in several applications, the standard model does not descri...
基于稀疏组LASSO约束的本征音子说话人自适应
说话人自适应 本征音子 组稀疏约束 稀疏组LASSO 约束 近点梯度法
2015/12/21
本征音子说话人自适应方法在自适应数据量不足时会出现严重的过拟合现象，提出了一种基于稀疏组
LASSO 约束的本征音子说话人自适应算法。首先给出隐马尔可夫—高斯混合模型下本征音子说话人自适应的基
本原理；然后将稀疏组LASSO 正则化引入到本征音子说话人自适应，通过调整权重因子控制模型的复杂度，并
通过一种加速近点梯度的数学优化算法来实现；最后将稀疏组LASSO 约束的自适应算法与当前多种正则...
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...
Learning interactions via hierarchical group-lasso regularization
hierarchical interaction computer intensive regression logistic
2015/8/21
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...
Network lasso: Clustering and optimization in large graphs
Convex Optimization ADMM Network Lasso
2015/8/7
Convex optimization is an essential tool for modern data analysis, as it provides a framework to formulate and solve many problems in machine learning and data mining. However, general convex optimiza...
Network Lasso: Clustering and Optimization in Large Graphs
Convex Optimization ADMM Network Lasso
2015/7/8
Convex optimization is an essential tool for modern data analysis, as it provides a framework to formulate and solve many problems in machine learning and data mining. However, general convex optimiza...
The lasso penalizes a least squares regression by the sum of the absolute values
(L1-norm) of the coefficients. The form of this penalty encourages sparse solutions (with many
coefficien...
A framework to characterize performance of LASSO algorithms
Noisy linear systems of equations LASSO SOCP ℓ 1 -optimization compressed sensing
2013/5/2
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...