Keyphrases
- laplacian eigenmaps
- manifold learning
- nonlinear dimensionality reduction
- kernel pca
- graph laplacian
- low dimensional
- locally linear embedding
- dynamic time warping
- dimensionality reduction
- empirical mode decomposition
- principal component analysis
- high dimensional data
- sparse representation
- kernel methods
- data sets
- random walk
- nearest neighbor
- high dimensional
- pattern recognition