Document Type

Journal Article

Department/Unit

Department of Mathematics

Title

Linearized alternating direction method of multipliers for sparse group and fused LASSO models

Language

English

Abstract

The least absolute shrinkage and selection operator (LASSO) has been playing an important role in variable selection and dimensionality reduction for linear regression. In this paper we focus on two general LASSO models: Sparse Group LASSO and Fused LASSO, and apply the linearized alternating direction method of multipliers (LADMM for short) to solve them. The LADMM approach is shown to be a very simple and efficient approach to numerically solve these general LASSO models. We compare it with some benchmark approaches on both synthetic and real datasets. © 2014 Elsevier B.V. All rights reserved.

Keywords

Alternating direction method of multipliers, Convex optimization, Least absolute shrinkage and selection operator, Linear regression, Variable selection

Publication Date

2014

Source Publication Title

Computational Statistics and Data Analysis

Volume

79

Start Page

203

End Page

221

Publisher

Elsevier

DOI

10.1016/j.csda.2014.05.017

Link to Publisher's Edition

http://dx.doi.org/10.1016/j.csda.2014.05.017

ISSN (print)

01679473

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