Fast nonlinear dimensionality reduction with topology representing networks.
Jakob J. VerbeekNikos A. VlassisBen J. A. KrösePublished in: ESANN (2002)
Keyphrases
- nonlinear dimensionality reduction
- manifold learning
- dimensionality reduction
- diffusion maps
- high dimensional data
- low dimensional
- dimensionality reduction methods
- maximum variance unfolding
- laplacian eigenmaps
- riemannian manifolds
- locally linear embedding
- computer vision
- pattern recognition
- support vector
- clustering algorithm
- feature selection
- data mining