Manifold learning with arbitrary norms.
Joe KileelAmit MoscovichNathan ZeleskoAmit SingerPublished in: CoRR (2020)
Keyphrases
- manifold learning
- dimensionality reduction
- low dimensional
- feature extraction
- high dimensional
- nonlinear dimensionality reduction
- diffusion maps
- subspace learning
- laplacian eigenmaps
- semi supervised
- head pose estimation
- high dimensional data
- dimension reduction
- manifold learning algorithm
- manifold structure
- locality preserving
- geodesic distance
- sparse representation
- riemannian manifolds
- locally linear embedding
- nearest neighbor
- locality preserving projections
- low dimensional manifolds
- similarity measure
- manifold embedding
- feature space
- data analysis
- neural network