Dimensionality Reduction Using the Sparse Linear Model.
Ioannis GkioulekasTodd E. ZicklerPublished in: NIPS (2011)
Keyphrases
- linear model
- dimensionality reduction
- high dimensional
- random projections
- least squares
- sparse representation
- regression model
- linear models
- low dimensional
- linear transformation
- feature extraction
- high dimensional data
- high dimensionality
- data representation
- principal component analysis
- data points
- feature space
- regression trees
- semi parametric
- additive model
- input space
- nonlinear models
- dimensionality reduction methods
- group lasso
- linear transformations
- linear discriminant analysis
- metric learning
- pattern recognition
- feature selection
- principal components
- machine learning
- markov chain
- video sequences