Multilinear Spatial Discriminant Analysis for Dimensionality Reduction.
Sen YuanXia MaoLijiang ChenPublished in: IEEE Trans. Image Process. (2017)
Keyphrases
- discriminant analysis
- dimensionality reduction
- linear discriminant analysis
- principal component analysis
- feature extraction
- dimensionality reduction methods
- subspace learning
- kernel discriminant analysis
- discriminant subspace
- fisher criterion
- face recognition
- dimension reduction
- high dimensional data
- higher order tensors
- graph embedding
- high dimensional
- discriminant projection
- pattern recognition
- principal components
- class separability
- singular value decomposition
- low dimensional
- unsupervised learning
- high dimensionality
- feature space
- partial least squares
- principal components analysis
- linear discriminant
- data representation
- random projections
- fisher linear discriminant analysis
- manifold learning
- factor analysis
- preprocessing step
- metric learning
- input space
- sparse representation
- fisher discriminant analysis
- feature selection
- multi class
- supervised dimensionality reduction
- data points
- low rank
- kernel trick
- null space
- locally linear embedding
- association rules