Discover latent discriminant information for dimensionality reduction: Non-negative Sparseness Preserving Embedding.
Wai Keung WongPublished in: Pattern Recognit. (2012)
Keyphrases
- discriminant information
- dimensionality reduction
- graph embedding
- latent space
- discriminant embedding
- linear discriminant analysis
- nonlinear dimensionality reduction
- principal component analysis
- low dimensional
- high dimensional
- subspace learning
- feature extraction
- high dimensional data
- manifold learning
- embedding space
- data points
- face recognition
- data representation
- feature space
- pattern recognition
- small sample size
- input space
- high dimensionality
- lower dimensional
- latent variables
- dimensionality reduction methods
- euclidean distance
- multidimensional scaling
- intrinsic dimensionality
- principal components
- discriminant analysis
- linear discriminant
- singular value decomposition
- feature selection
- locally linear embedding
- sparse representation
- computer vision
- null space
- manifold structure
- fisher criterion