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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.|
|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.|
|Pages:||489 - 493|
|Type of Material:||Journal Article|
|Journal/Proceeding Title:||Journal of Machine Learning Research|
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