Manifold learning in Wasserstein space.
Keaton HammCaroline MoosmüllerBernhard SchmitzerMatthew ThorpePublished in: CoRR (2023)
Keyphrases
- manifold learning
- low dimensional
- dimensionality reduction
- intrinsic manifold
- low dimensional manifolds
- high dimensional
- nonlinear dimensionality reduction
- diffusion maps
- embedding space
- high dimensional data
- geodesic distance
- subspace learning
- riemannian manifolds
- locality preserving
- laplacian eigenmaps
- semi supervised
- dimension reduction
- feature space
- latent space
- discriminant projection
- nonlinear manifold
- euclidean space
- head pose estimation
- manifold structure
- semi supervised learning
- manifold learning algorithm
- face recognition
- feature extraction
- lower dimensional
- pointwise
- data points
- principal component analysis
- locally linear embedding
- linear subspace
- data sets
- decision trees
- learning algorithm
- underlying manifold
- vector space
- sparse representation
- data mining