Dimensionality Reduction Using Kernel Pooled Local Discriminant Information.
Peng ZhangJing PengCarlotta DomeniconiPublished in: ICDM (2003)
Keyphrases
- discriminant information
- dimensionality reduction
- graph embedding
- feature space
- kernel pca
- input space
- linear discriminant analysis
- principal component analysis
- kernel learning
- data points
- high dimensional
- high dimensional data
- kernel function
- face recognition
- low dimensional
- kernel methods
- feature extraction
- subspace learning
- data representation
- small sample size
- high dimensionality
- feature selection
- manifold learning
- pattern recognition
- singular value decomposition
- dimensionality reduction methods
- discriminant analysis
- lower dimensional
- sparse representation
- object recognition
- principal components
- reproducing kernel hilbert space
- nonlinear dimensionality reduction
- null space
- dimension reduction
- similarity measure
- locally linear embedding
- linear discriminant