Unsupervised Kernel Dimension Reduction.
Meihong WangFei ShaMichael I. JordanPublished in: NIPS (2010)
Keyphrases
- dimension reduction
- unsupervised learning
- feature space
- principle component analysis
- principal component analysis
- feature extraction
- singular value decomposition
- high dimensional
- low dimensional
- high dimensional problems
- kernel function
- dimensionality reduction
- partial least squares
- kernel methods
- high dimensional data
- feature selection
- variable selection
- semi supervised
- manifold learning
- discriminative information
- data mining and machine learning
- cluster analysis
- supervised learning
- high dimensionality
- random projections
- linear discriminant analysis
- high dimensional data analysis
- preprocessing
- nearest neighbor
- data points
- kernel pca
- support vector
- image processing
- dimension reduction methods
- expectation maximization
- feature set
- learning algorithm
- manifold embedding
- machine learning