The fastclime Package for Linear Programming and Large-Scale Precision Matrix Estimation in R.
Author(s): Pang, Haotian; Liu, Han; Vanderbei, Robert J.
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Abstract: | We develop an R package fastclime for solving a family of regularized linear programming (LP) problems. Our package efficiently implements the parametric simplex algorithm, which provides a scalable and sophisticated tool for solving large-scale linear programs. As an illustrative example, one use of our LP solver is to implement an important sparse precision matrix estimation method called CLIME (Constrained L 1 Minimization Estimator). Compared with existing packages for this problem such as clime and flare, our package has three advantages: (1) it efficiently calculates the full piecewise-linear regularization path; (2) it provides an accurate dual certificate as stopping criterion; (3) it is completely coded in C and is highly portable. This package is designed to be useful to statisticians and machine learning researchers for solving a wide range of problems. |
Publication Date: | Feb-2014 |
Citation: | Pang, Haotian, Liu, Han, Vanderbei, Robert. "The fastclime Package for Linear Programming and Large-Scale Precision Matrix Estimation in R." Journal of Machine Learning Research, 15, 489 - 493, 2014. |
ISSN: | 1532-4435 |
Pages: | 489 - 493 |
Language: | ENG |
Type of Material: | Journal Article |
Journal/Proceeding Title: | Journal of Machine Learning Research |
Version: | This is the publisher’s version of the article (version of record). All rights reserved to the publisher. Please refer to the publisher's site for terms of use. |
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