HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projections.
Ines ChamiAlbert GuDat NguyenChristopher RéPublished in: CoRR (2021)
Keyphrases
- dimensionality reduction
- linear projection
- pattern recognition
- high dimensionality
- principal component analysis
- high dimensional data
- feature selection
- manifold learning
- feature extraction
- low dimensional
- dimensionality reduction methods
- input space
- data representation
- data points
- pattern recognition and machine learning
- three dimensional
- image reconstruction from projections
- singular value decomposition
- linear discriminant analysis
- high dimensional
- intrinsic dimensionality
- lower dimensional
- euclidean distance
- coordinate ascent
- polyhedral objects
- nonlinear dimensionality reduction
- random projections
- feature space
- sparse representation
- partial differential equations
- conservation laws
- principal components
- structure preserving
- optimization criterion
- tomographic reconstruction
- metric learning
- radon transform
- multidimensional scaling
- linear dimensionality reduction
- learning algorithm
- locally linear embedding
- face recognition
- convex sets