Keyphrases
- laplacian eigenmaps
- manifold learning
- kernel pca
- nonlinear dimensionality reduction
- graph laplacian
- dimensionality reduction
- empirical mode decomposition
- low dimensional
- dynamic time warping
- locally linear embedding
- euclidean space
- high dimensional
- support vector regression
- dimensionality reduction methods
- dimension reduction
- kernel methods
- support vector
- parameter space
- latent space
- vector space
- euclidean distance