| Literature DB >> 25620890 |
Haotian Pang1, Han Liu, Robert Vanderbei2.
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 L1 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.Entities:
Keywords: high dimensional data; linear programming; parametric simplex method; sparse precision matrix; undirected graphical model
Year: 2014 PMID: 25620890 PMCID: PMC4303570
Source DB: PubMed Journal: J Mach Learn Res ISSN: 1532-4435 Impact factor: 3.654