2014 JMLR JMLR 2014

The FASTCLIME Package for Linear Programming and Large-Scale Precision Matrix Estimation in R

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. [abs] [ pdf ][ bib ] [ code ] © JMLR 2014. (edit, beta)

🌉 Interdisciplinary Bridge — Machine Learning and Mathematics & Optimization
🧭 Keyword Pioneer — parametric simplex algorithm
🐣 Hot Topic Early Bird — linear programming
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy