Applications of Discriminative Dimensionality Reduction.
Barbara HammerAndrej GisbrechtAlexander SchulzPublished in: ICPRAM (2013)
Keyphrases
- dimensionality reduction
- class discrimination
- feature extraction
- unsupervised learning
- class separability
- feature selection
- high dimensional
- low dimensional
- latent space
- principal component analysis
- high dimensional data
- discriminative information
- high dimensionality
- pattern recognition
- subspace learning
- dimensionality reduction methods
- linear discriminant analysis
- input space
- feature space
- pattern recognition and machine learning
- data representation
- data points
- singular value decomposition
- manifold learning
- discriminative features
- lower dimensional
- dimension reduction
- structure preserving
- graph embedding
- linear projection
- learning algorithm
- linear dimensionality reduction
- metric learning
- principal components
- discriminant analysis
- kernel learning
- kernel pca
- discriminative power
- bayesian network classifiers
- sparse representation
- text categorization
- semi supervised
- feature vectors
- face recognition
- data sets
- supervised dimensionality reduction