Quadric hypersurface intersection for manifold learning in feature space.
Fedor PavutnitskiySergei O. IvanovEvgeny AbramovViacheslav BorovitskiyArtem KlochkovViktor VialovAnatolii ZaikovskiiAleksandr PetiushkoPublished in: CoRR (2021)
Keyphrases
- manifold learning
- feature space
- low dimensional
- dimensionality reduction
- high dimensional
- dimension reduction
- feature extraction
- nonlinear dimensionality reduction
- diffusion maps
- feature mapping
- input space
- high dimensionality
- riemannian manifolds
- subspace learning
- kernel function
- laplacian eigenmaps
- data points
- principal component analysis
- feature selection
- mean shift
- feature vectors
- support vector machine
- image representation
- high dimensional data
- linear discriminant analysis
- embedding space
- high dimensional feature space
- head pose estimation
- feature set
- geodesic distance
- manifold structure
- input data
- image retrieval
- manifold embedding
- low dimensional manifolds
- training set
- lower dimensional
- metric learning
- discriminating power
- unsupervised learning
- kernel methods
- dimensionality reduction methods
- data sets
- semi supervised
- decision trees
- learning algorithm