Semismooth Newton Coordinate Descent Algorithm for Elastic-Net Penalized Huber Loss Regression and Quantile Regression-Reference-Cited by-同舟云学术

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Semismooth Newton Coordinate Descent Algorithm for Elastic-Net Penalized Huber Loss Regression and Quantile Regression

Published:2017-05-26 Issue:3 Volume:26 Page:547-557
ISSN:1061-8600
Container-title:Journal of Computational and Graphical Statistics
language:en
Short-container-title:Journal of Computational and Graphical Statistics

Author:

Yi Congrui¹,Huang Jian¹

Affiliation:

1. Department of Statistics and Actuarial Science, University of Iowa, Iowa City, IA

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Discrete Mathematics and Combinatorics,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/10618600.2016.1256816

Reference26 articles.

1. Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection

2. High-Dimensional Statistics with a View Toward Applications in Biology

3. Smoothing Methods and Semismooth Methods for Nondifferentiable Operator Equations

4. Signal Recovery by Proximal Forward-Backward Splitting

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