A Grassmann-Rayleigh Quotient Iteration for Dimensionality Reduction in ICA.
Lieven De LathauwerLuc HoegaertsJoos VandewallePublished in: ICA (2004)
Keyphrases
- dimensionality reduction
- principal component analysis
- independent component analysis
- discriminant analysis
- neighborhood preserving
- feature extraction
- linear discriminant analysis
- graph embedding
- subspace learning
- face recognition
- low dimensional
- grassmann manifold
- high dimensional data
- principal components
- manifold learning
- independent components
- dimensionality reduction methods
- high dimensionality
- high dimensional
- data representation
- random projections
- dimension reduction
- linear dimensionality reduction
- data points
- pattern recognition
- independent components analysis
- machine intelligence
- preprocessing
- pattern recognition and machine learning
- blind source separation
- gaussian distribution
- factor analysis
- lower dimensional
- riemannian manifolds
- signal processing
- nonlinear dimensionality reduction
- log normal
- euclidean distance
- sar images
- linear subspace
- data sets
- objective function
- structure preserving
- feature selection
- machine learning
- source separation
- principle component analysis
- feature space
- feature vectors
- face images