Name
Abstract | ||
|---|---|---|
Dimension reduction is widely regarded as an effective way for decreasing the computation, storage, and communication loads of data-driven intelligent systems, leading to a growing demand for statistical methods that allow analysis (e.g., clustering) of compressed data. We therefore study in this paper a novel problem called compressive robust subspace clustering, which is to perform robust subspa... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TIP.2019.2917857 | IEEE Transactions on Image Processing |
Keywords | DocType | Volume |
Sparse matrices,Image coding,Sensors,Dimensionality reduction,Automation,Information science,Principal component analysis | Journal | 28 |
Issue | ISSN | Citations |
10 | 1057-7149 | 10 |
PageRank | References | Authors |
0.44 | 45 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guangcan Liu | 1 | 2515 | 76.85 |
| Zhao Zhang | 2 | 938 | 65.99 |
| QingShan Liu | 3 | 2625 | 162.58 |
| Hongkai Xiong | 4 | 512 | 82.84 |