Name
Title | ||
|---|---|---|
Rigorous optimisation of multilinear discriminant analysis with Tucker and PARAFAC structures. |
Abstract | ||
|---|---|---|
The proposed usage of manifold optimisation constitutes the first rigorous and monotonous optimisation approach for MDA methods and allows for MDA with the PARAFAC structure. Our results show that MDA methods applied to raw EEG data can extract discriminatory patterns when compared to traditional unsupervised multilinear feature extraction approaches, whereas the proposed PARAFAC structured MDA models provide meaningful patterns of activity. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s12859-018-2188-0 | BMC Bioinformatics |
Keywords | Field | DocType |
Classification,EEG,Electroencephalography,Multilinear discriminant analysis,Stiefel manifold,Tensor | Heuristic,Biology,Pattern recognition,Tensor,Stiefel manifold,Feature extraction,Artificial intelligence,Linear discriminant analysis,Genetics,Multilinear map,Manifold | Journal |
Volume | Issue | ISSN |
19 | 1 | 1471-2105 |
Citations | PageRank | References |
0 | 0.34 | 28 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laura Frølich | 1 | 2 | 0.74 |
| Tobias S. Andersen | 2 | 1 | 2.73 |
| Morten Mørup | 3 | 704 | 51.29 |