Information preserving and locally isometric&conformal embedding via Tangent Manifold Learning.
Alexander V. BernsteinAlexander P. KuleshovYury YanovichPublished in: DSAA (2015)
Keyphrases
- manifold learning
- information preserving
- nonlinear dimensionality reduction
- laplacian eigenmaps
- data embedding
- embedding space
- manifold embedding
- nonlinear manifold learning
- low dimensional
- locality preserving projections
- geodesic distance
- dimensionality reduction
- diffusion maps
- high dimensional
- semi supervised
- head pose estimation
- subspace learning
- dimension reduction
- low dimensional manifolds
- locally linear embedding
- latent space
- feature extraction
- discriminant embedding
- manifold structure
- locality preserving
- sparse representation
- high dimensional data
- feature selection
- graph embedding
- pattern recognition
- neural network
- riemannian manifolds
- vector space
- feature space
- preprocessing
- nonlinear manifold