GAITA: A Gauss-Seidel iterative thresholding algorithm for l(q) regularized least squares regression (vol 319, pg 220, 2017)

Zeng Jinshan; Peng Zhimin; Lin Shaobo

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GAITA: A Gauss-Seidel iterative thresholding algorithm for l(q) regularized least squares regression (vol 319, pg 220, 2017)

机译：Gaita：L（Q）规则化最小二乘回归的高斯 - 赛德尔迭代阈值算法（Vol 319，PG 220,2017）

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来源
《Journal of Computational and Applied Mathematics》 |2018年第2018期|共1页
作者
Zeng Jinshan; Peng Zhimin; Lin Shaobo;
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作者单位

Jiangxi Normal Univ Coll Comp Informat Engn Nanchang 330022 Jiangxi Peoples R China;

Univ Calif Los Angeles Dept Math Los Angeles CA 90095 USA;

Wenzhou Univ Coll Math &

Informat Sci Wenzhou 325035 Peoples R China;

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原文格式 PDF
正文语种 eng
中图分类计算数学;应用数学;
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1. GAITA: A Gauss-Seidel iterative thresholding algorithm for l(q) regularized least squares regression (vol 319, pg 220, 2017) [J] . Zeng Jinshan, Peng Zhimin, Lin Shaobo Journal of Computational and Applied Mathematics . 2018,第期

机译：Gaita：L（Q）规则化最小二乘回归的高斯 - 赛德尔迭代阈值算法（Vol 319，PG 220,2017）
2. A variable fixing version of the two-block nonlinear constrained Gauss-Seidel algorithm for ?_1-regularized least-squares [J] . Margherita Porcelli, Francesco Rinaldi Computational optimization and applications . 2014,第3期

机译：两块非线性约束Gauss-Seidel算法的可变固定版本，用于α_1正则化最小二乘
3. Comparison of principal components regression, partial least squares regression, multi-block partial least squares regression, and serial partial least squares regression algorithms for the analysis of Fe in iron ore using LIBS [J] . P. Yaroshchyk, D. L. Death, S. J. Spencer Journal of Analytical Atomic Spectrometry . 2012,第1期

机译：使用LIBS分析铁矿石中铁的主成分回归，偏最小二乘回归，多块偏最小二乘回归和串行偏最小二乘回归算法的比较
4. Locally regularized orthogonal least squares algorithm for the construction of sparse kernel regression models [C] . Sheng Chen International Conference on Signal Processing . 2002

机译：局部正常化的正交性最小二乘算法，用于稀疏内核回归模型的构建
5. Comparison of the ordinary least squares method and some regularization methods under multicollinearity in linear regression [D] . Huang, Yi. 2016

机译：线性回归中多重共线性下普通最小二乘法与某些正则化方法的比较
6. Accelerated fast iterative shrinkage thresholding algorithms for sparsity-regularized cone-beam CT image reconstruction [O] . Qiaofeng Xu, Deshan Yang, Jun Tan, -1

机译：稀疏正则化锥束CT图像重建的加速快速迭代收缩阈值算法
7. On the filtering effect of iterative regularization algorithms for linear least-squares problems [O] . Cornelio, Anastasia, Porta, Federica, Prato, Marco, 2013

机译：关于迭代正则化算法的滤波效果线性最小二乘问题
8. Parallelization of 'Gauss-Seidel' Algorithms as an Example of Parallel Iterative Equation Solving [R] . Dekker, L. 1987

机译：“Gauss-seidel”算法的并行化作为并行迭代方程求解的一个例子

GAITA: A Gauss-Seidel iterative thresholding algorithm for l(q) regularized least squares regression (vol 319, pg 220, 2017)

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