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| author | Liguros - Gitlab CI/CD [develop] <gitlab@liguros.net> | 2022-04-12 21:03:09 +0000 |
|---|---|---|
| committer | Liguros - Gitlab CI/CD [develop] <gitlab@liguros.net> | 2022-04-12 21:03:09 +0000 |
| commit | d97953e6ff67978da9554e7b4601aedceb21e215 (patch) | |
| tree | 674053c902db6972b9716c9ac3b1e960ee7a5358 /dev-R/RcppEnsmallen/metadata.xml | |
| parent | 1d1fa5bb30df70070bbbbd2b777b839d31f09c41 (diff) | |
| download | baldeagleos-repo-d97953e6ff67978da9554e7b4601aedceb21e215.tar.gz baldeagleos-repo-d97953e6ff67978da9554e7b4601aedceb21e215.tar.xz baldeagleos-repo-d97953e6ff67978da9554e7b4601aedceb21e215.zip | |
Adding metadata
Diffstat (limited to 'dev-R/RcppEnsmallen/metadata.xml')
| -rw-r--r-- | dev-R/RcppEnsmallen/metadata.xml | 29 |
1 files changed, 29 insertions, 0 deletions
diff --git a/dev-R/RcppEnsmallen/metadata.xml b/dev-R/RcppEnsmallen/metadata.xml new file mode 100644 index 000000000000..dab676e0246f --- /dev/null +++ b/dev-R/RcppEnsmallen/metadata.xml @@ -0,0 +1,29 @@ +<?xml version="1.0" encoding="UTF-8"?> +<!DOCTYPE pkgmetadata SYSTEM "http://www.gentoo.org/dtd/metadata.dtd"> +<pkgmetadata> + <maintainer type="person"> + <description>co-maintainers welcome</description> + <email>lssndrbarbieri@gmail.com</email> + <name>Alessandro Barbieri</name> + </maintainer> + <upstream> + <bugs-to>https://github.com/coatless/rcppensmallen/issues</bugs-to> + <doc lang="en">https://cran.r-project.org/web/packages/RcppEnsmallen/RcppEnsmallen.pdf</doc> + <changelog>https://cran.r-project.org/web/packages/RcppEnsmallen/ChangeLog</changelog> + <maintainer> + <name>James Joseph Balamuta</name> + <email>balamut2@illinois.edu</email> + </maintainer> + <remote-id type="github">coatless/rcppensmallen</remote-id> + </upstream> + <longdescription lang="en"> +Header-Only C++ Mathematical Optimization Library for 'Armadillo' +// 'Ensmallen' is a templated C++ mathematical optimization +library (by the 'MLPACK' team) that provides a simple set of +abstractions for writing an objective function to optimize. +Provided within are various standard and cutting-edge +optimizers that include full-batch gradient descent techniques, +small-batch techniques, gradient-free optimizers, and +constrained optimization. + </longdescription> +</pkgmetadata> |