Name
Abstract | ||
|---|---|---|
•A multi-view low-rank plus sparse subspace clustering algorithm is proposed.•Agreements are enforced between representations of the pairs of views or towards a common centroid.•Constrained convex optimization problem is for each view solved using alternating direction method of multipliers.•By solving related problem in reproducing kernel Hilbert space, kernel extension of the algorithm is derived.•Experimental results demonstrate that the proposed algorithm outperforms state-of-the-art multi-view subspace clustering algorithms. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.patcog.2017.08.024 | Pattern Recognition |
Keywords | DocType | Volume |
Subspace clustering,Multi-view data,Low-rank,Sparsity,Alternating direction method of multipliers,Reproducing kernel Hilbert space | Journal | 73 |
Issue | ISSN | Citations |
1 | 0031-3203 | 46 |
PageRank | References | Authors |
0.88 | 39 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maria Brbic | 1 | 46 | 1.55 |
| Ivica Kopriva | 2 | 146 | 16.60 |