Denoising and Dimension Reduction in Feature Space.
Mikio L. BraunJoachim M. BuhmannKlaus-Robert MüllerPublished in: NIPS (2006)
Keyphrases
- dimension reduction
- denoising
- feature space
- principal component analysis
- high dimensionality
- low dimensional
- high dimensional
- feature extraction
- linear discriminant analysis
- natural images
- high dimensional problems
- data mining and machine learning
- image processing
- random projections
- singular value decomposition
- feature selection
- high dimensional data
- dimensionality reduction
- manifold learning
- training samples
- discriminative information
- partial least squares
- high dimensional data analysis
- feature vectors
- input space
- data points
- training set
- unsupervised learning
- real world
- dimension reduction methods
- support vector machine
- discriminant analysis
- kernel methods
- multiple features
- cluster analysis
- pattern recognition
- high dimensional feature space
- kernel function