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".
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0 |
rolling source/ R- | GSparO_1.0.tar.gz |
3.4 KiB |
1.0 |
rolling linux/jammy R-4.5 | GSparO_1.0.tar.gz |
16.7 KiB |
1.0 |
rolling linux/noble R-4.5 | GSparO_1.0.tar.gz |
16.6 KiB |
1.0 |
latest source/ R- | GSparO_1.0.tar.gz |
3.4 KiB |
1.0 |
latest linux/jammy R-4.5 | GSparO_1.0.tar.gz |
16.7 KiB |
1.0 |
latest linux/noble R-4.5 | GSparO_1.0.tar.gz |
16.6 KiB |
1.0 |
2026-04-23 source/ R- | GSparO_1.0.tar.gz |
3.4 KiB |
1.0 |
2026-04-09 windows/windows R-4.5 | GSparO_1.0.zip |
19.4 KiB |
1.0 |
2025-04-20 source/ R- | GSparO_1.0.tar.gz |
3.4 KiB |