Keyphrases
- manifold learning
- data analysis
- laplacian eigenmaps
- high dimensional data
- low dimensional
- feature space
- dimensionality reduction
- nonlinear dimensionality reduction
- diffusion maps
- semi supervised
- high dimensional
- dimension reduction
- subspace learning
- riemannian manifolds
- kernel function
- head pose estimation
- feature extraction
- input space
- locally linear embedding
- kernel methods
- low dimensional manifolds
- cluster analysis
- geodesic distance
- machine learning
- kernel pca
- latent space
- nonlinear manifold
- discriminant projection
- kernel machines
- unsupervised learning
- data points
- data mining
- manifold structure
- least squares
- embedding space
- pairwise
- computer vision
- neural network