Efficiently updating and tracking the dominant kernel principal components.
Luc HoegaertsLieven De LathauwerIvan GoethalsJohan A. K. SuykensJoos VandewalleBart De MoorPublished in: Neural Networks (2007)
Keyphrases
- principal components
- kernel space
- principal component analysis
- principal component regression
- kernel principal component analysis
- multivariate data
- dimensionality reduction
- hyperplane
- kernel function
- feature space
- particle filter
- principal components analysis
- real time
- support vector
- dynamically updated
- spectral data
- input space
- covariance matrix
- kernel machines
- partial least squares
- feature set
- machine learning