An Efficient Approach to Sparse Linear Discriminant Analysis.
Luis Francisco Sánchez MerchanteYves GrandvaletGérard GovaertPublished in: ICML (2012)
Keyphrases
- linear discriminant analysis
- discriminant analysis
- face recognition
- dimensionality reduction
- principal component analysis
- feature extraction
- support vector
- sparse representation
- dimension reduction
- high dimensional
- null space
- discriminant features
- feature space
- high dimensional data
- small sample size
- support vector machine svm
- principal components analysis
- discriminative information
- multivariate statistical
- fisher criterion
- random projections
- sparse coding
- class separability
- fisher discriminant analysis
- subspace methods
- linear discriminant
- canonical correlation analysis
- machine learning
- low dimensional
- image classification
- locality preserving projections
- similarity measure
- face images
- qr decomposition
- feature vectors