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 |
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:
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