: A Novel Dimensionality Reduction for Euclidean and Hilbert Spaces.
Richard ConnorLucia VadicamoPublished in: ACM Trans. Knowl. Discov. Data (2024)
Keyphrases
- hilbert spaces
- dimensionality reduction
- euclidean distance
- hilbert space
- euclidean space
- variational inequalities
- low dimensional
- principal component analysis
- data points
- feature extraction
- high dimensionality
- high dimensional data
- high dimensional
- pattern recognition
- input space
- manifold learning
- feature selection
- feature space
- reproducing kernel hilbert space
- distance metric
- linear discriminant analysis
- principal components
- metric learning
- kernel pca
- finite dimensional