Name
Abstract | ||
|---|---|---|
Learning an expressive representation from multi-view data is a key step in various real-world applications. In this paper, we propose a semi-supervised multi-view deep discriminant representation learning (SMDDRL) approach. Unlike existing joint or alignment multi-view representation learning methods that cannot simultaneously utilize the consensus and complementary properties of multi-view data ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TPAMI.2020.2973634 | IEEE Transactions on Pattern Analysis and Machine Intelligence |
Keywords | DocType | Volume |
Redundancy,Feature extraction,Measurement,Machine learning,Taxonomy,Semisupervised learning | Journal | 43 |
Issue | ISSN | Citations |
7 | 0162-8828 | 3 |
PageRank | References | Authors |
0.37 | 18 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaodong Jia | 1 | 3 | 1.04 |
| Xiao-Yuan Jing | 2 | 769 | 55.18 |
| Xiaoke Zhu | 3 | 78 | 7.77 |
| Songcan Chen | 4 | 4148 | 191.89 |
| Bo Du | 5 | 114 | 19.71 |
| Ziyun Cai | 6 | 5 | 3.09 |
| He Zhenyu | 7 | 657 | 43.64 |
| Dong Yue | 8 | 3320 | 214.77 |