Discriminative Gaussian Process Latent Variable Model for Classification
Supervised learning is difficult with high dimensional input spacesand very small training sets, but accurate classification may bepossible if the data lie on a low-dimensional manifold. GaussianProcess Latent Variable Models can discover low dimensional manifoldsgiven only a small number of exampl...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Published: |
2007
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/1721.1/36901 |