Uniqueness theorems for kernel methods.
Christopher J. C. BurgesDavid J. CrispPublished in: Neurocomputing (2003)
Keyphrases
- kernel methods
- machine learning
- learning problems
- kernel function
- support vector machine
- support vector
- kernel matrix
- feature space
- kernel parameters
- sufficient conditions
- learning tasks
- reproducing kernel hilbert space
- kernel principal component analysis
- kernel pca
- multiple kernel learning
- multiple kernel
- kernel fisher discriminant analysis
- special case
- kernel matrices
- kernel based clustering
- kernel trick
- kernel ridge regression
- semidefinite programming
- learning theory
- dimensionality reduction
- active learning
- feature vectors
- high dimensional
- decision trees