High-Dimensional Fused Lasso Regression Using Majorization-Minimization and Parallel Processing

In this article, we propose a majorization-minimization (MM) algorithm for high-dimensional fused lasso regression (FLR) suitable for parallelization using graphics processing units (GPUs). The MM algorithm is stable and flexible as it can solve the FLR problems with various types of design matrices...

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Bibliographic Details

Published in:	Journal of computational and graphical statistics Vol. 24; no. 1; pp. 121 - 153
Main Authors:	Yu, Donghyeon, Won, Joong-Ho, Lee, Taehoon, Lim, Johan, Yoon, Sungroh
Format:	Journal Article
Language:	English
Published:	Alexandria Taylor & Francis 02.01.2015 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America Taylor & Francis Ltd
Subjects:	Algorithms Circuits Design engineering Graphics processing unit Majorization-minimization algorithm Parallel computation Parallel processing Regression Analysis Studies
ISSN:	1061-8600, 1537-2715
Online Access:	Get full text
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