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GSparO: Group Sparse Optimization

Approaches a group sparse solution of an underdetermined linear system. It implements the proximal gradient algorithm to solve a lower regularization model of group sparse learning. For details, please refer to the paper "Y. Hu, C. Li, K. Meng, J. Qin and X. Yang. Group sparse optimization via l_{p,q} regularization. Journal of Machine Learning Research, to appear, 2017".

Version: 1.0
Depends: R (≥ 3.3.1)
Imports: stats, ThreeWay, ggplot2
Published: 2017-02-20
DOI: 10.32614/CRAN.package.GSparO
Author: Yaohua Hu [aut, cre, cph], Xinlin Hu [trl]
Maintainer: Yaohua Hu <mayhhu at szu.edu.cn>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: GSparO results

Documentation:

Reference manual: GSparO.pdf

Downloads:

Package source: GSparO_1.0.tar.gz
Windows binaries: r-devel: GSparO_1.0.zip, r-release: GSparO_1.0.zip, r-oldrel: GSparO_1.0.zip
macOS binaries: r-release (arm64): GSparO_1.0.tgz, r-oldrel (arm64): GSparO_1.0.tgz, r-release (x86_64): GSparO_1.0.tgz, r-oldrel (x86_64): GSparO_1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=GSparO to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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