lbfgs: Limited-memory BFGS Optimization

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.

Install the latest version of this package by entering the following in R:
install.packages("lbfgs")
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 <acoppola@college.harvard.edu>
LicenseGPL (>= 2)
Version1.2.1

View on CRAN

Files

inst
inst/doc
inst/doc/Vignette.Rnw
inst/doc/Vignette.pdf
src
src/arithmetic_sse_double.h
src/arithmetic_ansi.h
src/lbfgs.cc
src/arithmetic_sse_float.h
src/evaluate.h
src/RcppExports.cpp
src/lbfgs.h
NAMESPACE
data
data/Leukemia.RData
data/datalist
R
R/lbfgs.R
vignettes
vignettes/CppMB.pdf
vignettes/Vignette.Rnw
vignettes/biblio.bib
README.md
MD5
build
build/vignette.rds
DESCRIPTION
man
man/Leukemia.Rd man/lbfgs.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

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