A Nonlinear Approach to Dimension Reduction.
Lee-Ad GottliebRobert KrauthgamerPublished in: Discret. Comput. Geom. (2015)
Keyphrases
- dimension reduction
- manifold embedding
- feature extraction
- principal component analysis
- nonlinear manifold
- high dimensional
- high dimensional problems
- manifold learning
- singular value decomposition
- random projections
- feature selection
- linear discriminant analysis
- partial least squares
- high dimensional data
- variable selection
- high dimensionality
- low dimensional
- discriminative information
- data mining and machine learning
- high dimensional data analysis
- dimensionality reduction
- feature space
- unsupervised learning
- preprocessing
- kernel pca
- sparse metric learning
- data sets
- knowledge discovery
- probabilistic model
- optical flow
- data analysis
- object recognition
- image processing
- learning algorithm
- machine learning