咨询与建议

限定检索结果

文献类型

  • 49 篇 期刊文献
  • 14 篇 会议

馆藏范围

  • 63 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 42 篇 理学
    • 33 篇 统计学(可授理学、...
    • 8 篇 数学
    • 4 篇 物理学
    • 2 篇 生物学
    • 1 篇 地理学
    • 1 篇 地球物理学
    • 1 篇 系统科学
  • 34 篇 工学
    • 22 篇 计算机科学与技术...
    • 9 篇 电气工程
    • 8 篇 信息与通信工程
    • 2 篇 仪器科学与技术
    • 1 篇 电子科学与技术(可...
    • 1 篇 控制科学与工程
    • 1 篇 测绘科学与技术
  • 20 篇 经济学
    • 19 篇 应用经济学
    • 1 篇 理论经济学
  • 3 篇 农学
    • 1 篇 作物学
  • 3 篇 医学
    • 3 篇 临床医学
    • 1 篇 基础医学(可授医学...
  • 3 篇 管理学
    • 2 篇 管理科学与工程(可...
    • 1 篇 图书情报与档案管...
  • 1 篇 教育学
    • 1 篇 心理学(可授教育学...

主题

  • 63 篇 coordinate desce...
  • 9 篇 variable selecti...
  • 8 篇 lasso
  • 6 篇 generalized fuse...
  • 4 篇 oracle property
  • 3 篇 penalized likeli...
  • 3 篇 spatio-temporal ...
  • 3 篇 bayesian algorit...
  • 3 篇 penalized least ...
  • 3 篇 high-dimensional...
  • 3 篇 altimetry
  • 2 篇 features selecti...
  • 2 篇 power allocation
  • 2 篇 shrinkage
  • 2 篇 model selection
  • 2 篇 bic
  • 2 篇 additive poisson...
  • 2 篇 total variation
  • 2 篇 elastic net
  • 2 篇 adaptive lasso

机构

  • 5 篇 korea univ dept ...
  • 3 篇 korea univ dept ...
  • 3 篇 chungbuk natl un...
  • 2 篇 univ minnesota d...
  • 2 篇 univ rochester d...
  • 2 篇 cukurova univ fa...
  • 2 篇 hiroshima univ g...
  • 2 篇 hiroshima univ e...
  • 1 篇 univ n carolina ...
  • 1 篇 graduate school ...
  • 1 篇 cukurova univ fa...
  • 1 篇 lakireddy bali r...
  • 1 篇 radiat effects r...
  • 1 篇 univ lisbon inst...
  • 1 篇 southwest jiaoto...
  • 1 篇 univ essex sch c...
  • 1 篇 univ michigan de...
  • 1 篇 chungbuk natl un...
  • 1 篇 harvard univ dep...
  • 1 篇 georgia state un...

作者

  • 8 篇 jhong jae-hwan
  • 8 篇 koo ja-yong
  • 7 篇 ohishi mineaki
  • 6 篇 yanagihara hirok...
  • 4 篇 yamamura mariko
  • 3 篇 genc murat
  • 3 篇 lee jungjun
  • 3 篇 ozkale m. revan
  • 3 篇 halimi abderrahi...
  • 3 篇 bak kwan-young
  • 2 篇 oualkacha karim
  • 2 篇 wu tong tong
  • 2 篇 okamura kensuke
  • 2 篇 shin jae-kyung
  • 2 篇 itoh yoshimichi
  • 2 篇 hirose kei
  • 2 篇 ouhourane mohame...
  • 2 篇 honeine paul
  • 1 篇 mineaki ohishi
  • 1 篇 lv yazhao

语言

  • 59 篇 英文
  • 4 篇 其他
检索条件"主题词=Coordinate descent algorithm"
63 条 记 录,以下是41-50 订阅
排序:
Automatic structure discovery for varying-coefficient partially linear models
收藏 引用
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 2017年 第15期46卷 7703-7716页
作者: Yang, Guangren Sun, Yanqing Cui, Xia Jinan Univ Sch Econ Dept Stat Guangzhou Guangdong Peoples R China Univ N Carolina Dept Math & Stat Charlotte NC USA Guangzhou Univ Sch Econ & Stat Guangzhou 510006 Guangdong Peoples R China
Varying-coefficient partially linear models provide a useful tools for modeling of covariate effects on the response variable in regression. One key question in varying-coefficient partially linear models is the choic... 详细信息
来源: 评论
Penalized B-spline estimator for regression functions using total variation penalty
收藏 引用
JOURNAL OF STATISTICAL PLANNING AND INFERENCE 2017年 184卷 77-93页
作者: Jhong, Jae-Hwan Koo, Ja-Yong Lee, Seong-Whan Korea Univ Dept Stat Seoul 136701 South Korea Korea Univ Dept Brain & Cognit Engn Seoul 136701 South Korea
We carry out a study on a penalized regression spline estimator with total variation penalty. In order to provide a spatially adaptive method, we consider total variation penalty for the estimating regression function... 详细信息
来源: 评论
Bayesian Estimation of Smooth Altimetric Parameters: Application to Conventional and Delay/Doppler Altimetry
收藏 引用
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2016年 第4期54卷 2207-2219页
作者: Halimi, Abderrahim Mailhes, Corinne Tourneret, Jean-Yves Snoussi, Hichem Univ Technol Troyes Inst Charles Delaunay CNRS F-10010 Troyes France Univ Toulouse IRIT INPENSEEIHT TeSA F-31071 Toulouse France
This paper proposes a new Bayesian strategy for the smooth estimation of altimetric parameters. The altimetric signal is assumed to be corrupted by a thermal and speckle noise distributed according to an independent a... 详细信息
来源: 评论
Reinforced Angle-Based Multicategory Support Vector Machines
收藏 引用
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS 2016年 第3期25卷 806-825页
作者: Zhang, Chong Liu, Yufeng Wang, Junhui Zhu, Hongtu Univ Waterloo Dept Stat & Actuarial Sci Waterloo ON N2L 3G1 Canada Univ North Carolina Chapel Hill Dept Stat & Operat Res Dept Genet Chapel Hill NC 28223 USA Univ North Carolina Chapel Hill Dept Biostat Chapel Hill NC 28223 USA City Univ Hong Kong Dept Math Hong Kong Hong Kong Peoples R China Univ North Carolina Chapel Hill Dept Biostat Chapel Hill NC 28223 USA
The support vector machine (SVM) is a very popular classification tool with many successful applications. It was originally designed for binary problems with desirable theoretical properties. Although there exist vari... 详细信息
来源: 评论
The shooting S-estimator for robust regression
收藏 引用
COMPUTATIONAL STATISTICS 2016年 第3期31卷 829-844页
作者: Ollerer, Viktoria Alfons, Andreas Croux, Christophe Katholieke Univ Leuven Fac Econ & Business Naamsestr 69 B-3000 Louvain Belgium Erasmus Univ Erasmus Sch Econ POB 1738 NL-3000 DR Rotterdam Netherlands
To perform multiple regression, the least squares estimator is commonly used. However, this estimator is not robust to outliers. Therefore, robust methods such as S-estimation have been proposed. These estimators flag... 详细信息
来源: 评论
Customized algorithms for growing connected resistive networks
Customized algorithms for growing connected resistive networ...
收藏 引用
10th IFAC Symposium on Nonlinear Control Systems (NOLCOS)
作者: Moghaddam, Sepideh Hassan Juvanovic, Mihailo R. Univ Minnesota Dept Elect & Comp Engn Minneapolis MN 55455 USA
We consider the problem of adding edges to connected resistive networks in order to optimally enhance their performance. The performance is captured by the H-2 norm of the closed-loop network and the l(1) regularizati... 详细信息
来源: 评论
FILTERING SMOOTH ALTIMETRIC SIGNALS USING A BAYESIAN algorithm  24
FILTERING SMOOTH ALTIMETRIC SIGNALS USING A BAYESIAN ALGORIT...
收藏 引用
24th European Signal Processing Conference (EUSIPCO)
作者: Halimi, Abderrahim Buller, Gerald McLaughlin, Steve Honeine, Paul Heriot Watt Univ Sch Engn & Phys Sci Edinburgh Midlothian Scotland Normandie Univ UNIROUEN UNIHAVRE INSA RouenLITIS Rouen France
This paper presents a new Bayesian strategy for the estimation of smooth signals corrupted by Gaussian noise. The method assumes a smooth evolution of a succession of continuous signals that can have a numerical or an... 详细信息
来源: 评论
K-nearest neighbors and a kernel density estimator for GEFCom2014 probabilistic wind power forecasting
收藏 引用
INTERNATIONAL JOURNAL OF FORECASTING 2016年 第3期32卷 1074-1080页
作者: Zhang, Yao Wang, Jianxue Xi An Jiao Tong Univ Sch Elect Engn Xian 710049 Peoples R China
Probabilistic forecasts provide quantitative information in relation to energy uncertainty, which is essential for making better decisions on the operation of power systems with an increasing penetration of wind power... 详细信息
来源: 评论
Hyperspectral Unmixing in Presence of Endmember Variability, Nonlinearity, or Mismodeling Effects
收藏 引用
IEEE TRANSACTIONS ON IMAGE PROCESSING 2016年 第10期25卷 4565-4579页
作者: Halimi, Abderrahim Honeine, Paul Bioucas-Dias, Jose M. Heriot Watt Univ Sch Engn & Phys Sci Edinburgh EH14 4AS Midlothian Scotland Univ Rouen Lab Informat Traitement Informat & Syst Normandie Univ F-76000 Rouen France Univ Lisbon Inst Telecomunicacoes P-1049001 Lisbon Portugal Univ Lisbon Inst Super Tecn P-1049001 Lisbon Portugal
This paper presents three hyperspectral mixture models jointly with Bayesian algorithms for supervised hyperspectral unmixing. Based on the residual component analysis model, the proposed general formulation assumes t... 详细信息
来源: 评论
Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structure
收藏 引用
BIOMETRICS 2015年 第2期71卷 354-363页
作者: Li, Yanming Nan, Bin Zhu, Ji Univ Michigan Dept Biostat Ann Arbor MI 48109 USA Univ Michigan Dept Stat Ann Arbor MI 48109 USA
We propose a multivariate sparse group lasso variable selection and estimation method for data with high-dimensional predictors as well as high-dimensional response variables. The method is carried out through a penal... 详细信息
来源: 评论