Multilinear (Tensor) ICA and Dimensionality Reduction.
M. Alex O. VasilescuDemetri TerzopoulosPublished in: ICA (2007)
Keyphrases
- dimensionality reduction
- higher order tensors
- principal component analysis
- independent component analysis
- independent components analysis
- feature extraction
- neighborhood preserving
- independent components
- low dimensional
- high dimensional data
- subspace learning
- data representation
- feature space
- pattern recognition
- tensor analysis
- lower dimensional
- face recognition
- data points
- high dimensionality
- singular value decomposition
- factor analysis
- neighborhood preserving embedding
- high dimensional
- linear discriminant analysis
- statistical independence
- random projections
- tensor decomposition
- discriminant analysis
- linear dimensionality reduction
- sparse representation
- signal processing
- dimensionality reduction methods
- metric learning
- manifold learning
- principal components
- pattern recognition and machine learning
- neural network
- structure preserving
- locally linear embedding
- blind source separation
- negative matrix factorization
- feature vectors
- nonlinear dimensionality reduction
- preprocessing
- graph embedding
- principle component analysis
- kernel pca
- supervised dimensionality reduction
- higher order singular value decomposition
- euclidean space