Name
Abstract | ||
|---|---|---|
Generalized eigenvalue proximal support vector machines (GEPSVMs) are a simple and effective binary classification method in which each hyperplane is closest to one of the two classes and as far as possible from the other class. They solve a pair of generalized eigenvalue problems to obtain two nonparallel hyperplanes. Multiview learning considers learning with multiple feature sets to improve the... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TCYB.2017.2786719 | IEEE Transactions on Cybernetics |
Keywords | Field | DocType |
Eigenvalues and eigenfunctions,Optimization,Support vector machines,Sun,Web pages,Standards,Symmetric matrices | Mathematical optimization,Binary classification,Support vector machine,Algorithm,Symmetric matrix,Eigendecomposition of a matrix,Hyperplane,Kernel method,Optimization problem,Eigenvalues and eigenvectors,Mathematics | Journal |
Volume | Issue | ISSN |
49 | 2 | 2168-2267 |
Citations | PageRank | References |
15 | 0.55 | 13 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shiliang Sun | 1 | 1732 | 115.55 |
| Xijiong Xie | 2 | 51 | 2.72 |
| Chao Dong | 3 | 2064 | 80.72 |