Name
Title | ||
|---|---|---|
Semi-supervised feature selection with exploiting shared information among multiple tasks. |
Abstract | ||
|---|---|---|
•A semi-supervised and multi-task feature learning framework is proposed.•The proposed algorithm is suitable for large-scale dataset.•We propose an efficient iterative algorithm to optimize the objective function. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.jvcir.2016.10.007 | Journal of Visual Communication and Image Representation |
Keywords | Field | DocType |
Semi-supervised learning,Feature selection,Multi-task learning,Face recognition,3D motion data analysis,Spoken letter recognition,Handwritten digits recognition | Facial recognition system,Semi-supervised learning,Multi-task learning,Pattern recognition,Feature selection,Feature (computer vision),Iterative method,Computer science,Supervised learning,Feature (machine learning),Artificial intelligence,Machine learning | Journal |
Volume | ISSN | Citations |
41 | 1047-3203 | 1 |
PageRank | References | Authors |
0.35 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaodong Wang | 1 | 35 | 5.19 |
| Rung-Ching Chen | 2 | 331 | 37.37 |
| Fei Yan | 3 | 2 | 0.70 |
| Zhiqiang Zeng | 4 | 139 | 16.35 |