A Nonlinear Approach to Dimension Reduction.
Lee-Ad GottliebRobert KrauthgamerPublished in: SODA (2011)
Keyphrases
- dimension reduction
- manifold embedding
- principal component analysis
- feature extraction
- high dimensional
- singular value decomposition
- high dimensional problems
- feature selection
- data mining and machine learning
- linear discriminant analysis
- nonlinear manifold
- random projections
- manifold learning
- low dimensional
- high dimensionality
- cluster analysis
- partial least squares
- dimensionality reduction
- high dimensional data analysis
- dimension reduction methods
- preprocessing
- feature space
- high dimensional data
- variable selection
- unsupervised learning
- kernel pca
- discriminative information
- model selection
- high dimensional feature space
- real world
- pattern recognition
- sparse representation