Name
Abstract | ||
|---|---|---|
Finding the informative subspaces of high-dimensional datasets is at the core of numerous applications in computer vision, where spectral-based subspace clustering is arguably the most widely studied method due to its strong empirical performance. Such algorithms first compute an affinity matrix to construct a self-representation for each sample using other samples as a dictionary. Sparsity and co... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TPAMI.2019.2913863 | IEEE Transactions on Pattern Analysis and Machine Intelligence |
Keywords | DocType | Volume |
Clustering algorithms,Sparse matrices,Correlation,Clustering methods,Optimization,Minimization,Matching pursuit algorithms | Journal | 42 |
Issue | ISSN | Citations |
6 | 0162-8828 | 5 |
PageRank | References | Authors |
0.38 | 18 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jufeng Yang | 1 | 61 | 9.97 |
| jie liang | 2 | 26 | 10.90 |
| Kai Wang | 3 | 1734 | 195.03 |
| Paul L. Rosin | 4 | 2559 | 254.25 |
| Yang Ming-Hsuan | 5 | 15303 | 620.69 |