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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 |
| 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 |
| Reference manual: | GSparO.pdf |
| 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 |
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