Regaining sparsity in kernel principal components.
César Ignacio García-OsorioColin FyfePublished in: Neurocomputing (2005)
Keyphrases
- principal components
- kernel space
- kernel principal component analysis
- principal component analysis
- principal component regression
- dimensionality reduction
- multivariate data
- high dimensional
- hyperplane
- feature space
- sparse representation
- covariance matrix
- kernel methods
- spectral data
- principal components analysis
- kernel function
- feature set
- support vector
- multiple kernel learning
- kernel pca
- pattern recognition
- input space
- data sets
- kernel matrix
- kernel machines
- training data
- face recognition