Dimensionality reduction by rank preservation.
Victor OnclinxJohn Aldo LeeVincent WertzMichel VerleysenPublished in: IJCNN (2010)
Keyphrases
- dimensionality reduction
- high dimensional
- principal component analysis
- feature extraction
- low dimensional
- high dimensional data
- subspace learning
- data points
- data representation
- pattern recognition
- principal components
- manifold learning
- feature space
- kernel pca
- structure preserving
- input space
- linear dimensionality reduction
- pattern recognition and machine learning
- euclidean distance
- linear discriminant analysis
- dimensionality reduction methods
- singular value decomposition
- feature selection
- random projections
- genetic algorithm
- nonlinear dimensionality reduction
- rank aggregation
- principal components analysis
- preprocessing step
- metric learning
- linear projection
- high dimensionality
- data mining
- computer vision
- dimension reduction
- kernel learning
- digital objects
- euclidean space
- discriminant analysis