lbfgs: Limited-memory BFGS Optimization
Version 1.2.1

A wrapper built around the libLBFGS optimization library by Naoaki Okazaki. The lbfgs package implements both the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) and the Orthant-Wise Quasi-Newton Limited-Memory (OWL-QN) optimization algorithms. The L-BFGS algorithm solves the problem of minimizing an objective, given its gradient, by iteratively computing approximations of the inverse Hessian matrix. The OWL-QN algorithm finds the optimum of an objective plus the L1-norm of the problem's parameters. The package offers a fast and memory-efficient implementation of these optimization routines, which is particularly suited for high-dimensional problems.

Package details

AuthorAntonio Coppola [aut, cre, cph], Brandon Stewart [aut, cph], Naoaki Okazaki [aut, cph], David Ardia [ctb, cph], Dirk Eddelbuettel [ctb, cph], Katharine Mullen [ctb, cph], Jorge Nocedal [ctb, cph]
Date of publication2014-08-31 11:23:32
MaintainerAntonio Coppola <[email protected]>
LicenseGPL (>= 2)
Version1.2.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("lbfgs")

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lbfgs documentation built on May 29, 2017, 4:08 p.m.