megaman: Manifold Learning with Millions of points.
James McQueenMarina MeilaJacob VanderPlasZhongyue ZhangPublished in: CoRR (2016)
Keyphrases
- manifold learning
- geodesic distance
- dimensionality reduction
- intrinsic manifold
- semi supervised
- low dimensional
- nonlinear dimensionality reduction
- subspace learning
- high dimensional
- high dimensional data
- principal curves
- feature extraction
- data points
- laplacian eigenmaps
- point sets
- diffusion maps
- dimension reduction
- manifold learning algorithm
- feature points
- low dimensional manifolds
- head pose estimation
- feature space
- sparse representation
- signal processing
- multiscale
- locality preserving
- manifold embedding
- discriminant projection
- computer vision
- pattern recognition
- locally linear embedding
- riemannian manifolds
- least squares
- principal component analysis