Sparse Features for PCA-Like Linear Regression.
Christos BoutsidisPetros DrineasMalik Magdon-IsmailPublished in: NIPS (2011)
Keyphrases
- linear regression
- sparse regression
- feature extraction
- least squares
- feature space
- principal component analysis
- generalized linear models
- sparse pca
- regression methods
- high dimensional
- feature vectors
- linear regression model
- ridge regression
- canonical correlation analysis
- principal components
- svm classifier
- feature set
- dimensionality reduction
- regression problems
- principal components analysis
- locally weighted
- feature selection and classification
- random projections
- feature selection
- singular value decomposition
- sparse representation
- face recognition