Perturbation Bounds for Procrustes, Classical Scaling, and Trilateration, with Applications to Manifold Learning.
Ery Arias-CastroAdel JavanmardBruno PelletierPublished in: CoRR (2018)
Keyphrases
- manifold learning
- low dimensional
- dimensionality reduction
- diffusion maps
- dimension reduction
- nonlinear dimensionality reduction
- high dimensional
- semi supervised
- subspace learning
- high dimensional data
- feature extraction
- laplacian eigenmaps
- head pose estimation
- discriminant projection
- manifold structure
- low dimensional manifolds
- locality preserving
- data points
- feature space
- manifold embedding
- locally linear embedding
- riemannian manifolds
- nearest neighbor
- knn
- pattern recognition