From Principal Subspaces to Principal Components with Linear Autoencoders.
Elad PlautPublished in: CoRR (2018)
Keyphrases
- principal components
- principal component analysis
- linear features
- dimensionality reduction
- hilbert space
- kernel principal component analysis
- kernel space
- multivariate data
- grassmann manifold
- high dimensional data
- principal components analysis
- low dimensional
- hyperplane
- denoising
- singular value decomposition
- high dimensional
- pattern recognition
- linear subspace
- covariance matrix
- spectral data
- independent component analysis
- feature space
- dimension reduction
- independent components
- weight vector
- data mining
- principal component regression
- manifold learning
- original data
- discriminant analysis
- linear discriminant analysis
- feature set
- nearest neighbor
- face recognition
- decision trees