Name
Abstract | ||
|---|---|---|
•An ℓ2,1-2 self-representation unsupervised feature selection is proposed.•ℓ2,1-2 is proved to guarantee the sparsity of selection matrix in theory.•An iterative CCCP algorithm is designed to tackle the nonconvexity of ℓ2,1-2.•The global convergence of our CCCP is theoretically analyzed.•Extensive experimental results verify the effectiveness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.eswa.2021.114643 | Expert Systems with Applications |
Keywords | DocType | Volume |
Unsupervised feature selection,Self-representation,Non-convex regularization,CCCP,ADMM | Journal | 173 |
ISSN | Citations | PageRank |
0957-4174 | 1 | 0.35 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianyu Miao | 1 | 4 | 2.07 |
| Yuan Ping | 2 | 6 | 3.16 |
| Zhensong Chen | 3 | 4 | 2.09 |
| Xiao-Bo Jin | 4 | 105 | 12.67 |
| Peijia Li | 5 | 4 | 1.41 |
| Lingfeng Niu | 6 | 83 | 18.24 |