Minimax Estimation of Distances on a Surface and Minimax Manifold Learning in the Isometric-to-Convex Setting.
Ery Arias-CastroPhong Alain ChauPublished in: CoRR (2020)
Keyphrases
- manifold learning
- geodesic distance
- low dimensional
- dimensionality reduction
- semi supervised
- high dimensional
- diffusion maps
- laplacian eigenmaps
- nonlinear dimensionality reduction
- feature extraction
- dimension reduction
- subspace learning
- high dimensional data
- head pose estimation
- neural network
- sparse representation
- d objects
- riemannian manifolds
- locally linear embedding
- euclidean space
- manifold structure
- intrinsic dimensionality
- embedding space
- support vector
- low dimensional manifolds