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.

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

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Files

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