Extensions of Manifold Learning Algorithms in Kernel Feature Space.
Yaoliang YuPeng GuanLiming ZhangPublished in: ISNN (1) (2007)
Keyphrases
- feature space
- kernel function
- kernel methods
- input space
- kernel space
- high dimensional feature space
- high dimensional
- dot product
- kernel matrix
- kernel pca
- kernel trick
- mean shift
- feature vectors
- principal component analysis
- feature selection
- training set
- high dimensionality
- classification accuracy
- image representation
- graph kernels
- class separability
- training samples
- gaussian kernels
- dimensionality reduction
- support vector machine
- feature extraction
- data points
- image retrieval
- linear discriminant analysis
- dimension reduction
- hyperplane
- support vector
- kernel principal component analysis
- linearly separable
- rbf kernel
- mercer kernel
- data sets
- kernel machines
- dissimilarity measure
- spectral clustering
- low dimensional
- pairwise
- machine learning