A soft label based linear discriminant analysis for semi-supervised dimensionality reduction.
Ming-Bo ZhaoZhao ZhangZhao ZhangPublished in: IJCNN (2013)
Keyphrases
- linear discriminant analysis
- semi supervised dimensionality reduction
- dimensionality reduction
- discriminant analysis
- graph embedding
- label information
- high dimensional data
- principal component analysis
- semi supervised
- dimension reduction
- high dimensional
- pattern recognition and machine learning
- small sample size
- feature extraction
- face recognition
- fisher criterion
- data representation
- manifold learning
- subspace learning
- pattern recognition
- support vector machine svm
- feature selection
- low dimensional
- feature space
- principal components
- data points
- null space
- singular value decomposition
- class labels
- high dimensionality
- scatter matrix
- unsupervised learning
- support vector
- neural network
- image processing
- nearest neighbor
- metric learning
- input data
- latent dirichlet allocation
- labeled data
- training samples
- sparse representation