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>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: GSparO results


Reference manual: GSparO.pdf


Package source: GSparO_1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


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