Polynomial approximate discretization of geometric centers in high-dimensional Euclidean space.
Vladimir ShenmaierPublished in: Adv. Data Anal. Classif. (2022)
Keyphrases
- euclidean space
- high dimensional
- low dimensional
- metric space
- discrete space
- data points
- embedding space
- dimensionality reduction
- similarity search
- riemannian manifolds
- high dimensional data
- vector space
- euclidean distance
- shape analysis
- lie group
- geometric structure
- quadratic form
- reproducing kernel hilbert space
- principal component analysis
- tangent space
- nearest neighbor
- parameter space
- multi dimensional scaling
- input space
- manifold learning
- multi dimensional
- constant curvature
- dimensional euclidean space
- laplace beltrami
- pairwise distances
- fisher information
- geodesic distance
- graph laplacian
- multidimensional scaling
- point sets
- pairwise
- feature space
- machine learning