Arbitrariness of Outward Closeness in Laplacian Dimensionality Reduction.
Jirí JanecekIrina PerfilievaPublished in: EUSFLAT/AGOP (2023)
Keyphrases
- dimensionality reduction
- high dimensional
- low dimensional
- high dimensional data
- pattern recognition
- principal component analysis
- high dimensionality
- data representation
- input space
- feature space
- nonlinear dimensionality reduction
- euclidean distance
- structure preserving
- manifold learning
- random projections
- principal components
- feature selection
- sparse representation
- data points
- feature extraction
- video matting
- kernel pca
- dimensionality reduction methods
- linear dimensionality reduction
- linear projection
- pattern recognition and machine learning
- differential operators
- sparse coding
- metric learning
- dimension reduction
- linear discriminant analysis
- lower dimensional
- neural network
- image classification
- image processing
- semi supervised dimensionality reduction