Optimality in high-dimensional tensor discriminant analysis.
Keqian MinQing MaiJunge LiPublished in: Pattern Recognit. (2023)
Keyphrases
- discriminant analysis
- high dimensional
- dimensionality reduction
- linear discriminant analysis
- feature extraction
- low dimensional
- kernel principal component analysis
- principal component analysis
- high dimensional data
- high dimensionality
- small sample size
- feature space
- dimension reduction
- fisher criterion
- graph embedding
- generalized linear
- fisher linear discriminant analysis
- higher order tensors
- face recognition
- dimensionality reduction methods
- data points
- cluster analysis
- lower dimensional
- fisher discriminant analysis
- pattern recognition
- image processing
- kernel discriminant analysis
- nearest neighbor
- input space
- computer vision
- partial least squares
- diffusion tensor
- data sets
- knowledge discovery
- subspace learning
- manifold learning