Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions.
Carl-Johann Simon-GabrielBernhard SchölkopfPublished in: J. Mach. Learn. Res. (2018)
Keyphrases
- kernel function
- kernel methods
- multiple kernel learning
- kernel learning
- reproducing kernel hilbert space
- positive definite
- multiple kernel
- feature space
- string kernels
- support vector
- polynomial kernels
- kernel matrices
- kernel machines
- graph kernels
- gaussian kernel
- convolution kernel
- kernel matrix
- gram matrix
- hilbert space
- kernel parameters
- optimal kernel
- kernel trick
- rbf kernel
- positive semidefinite
- gaussian kernels
- support vector machine
- histogram intersection kernel
- probability distribution
- euclidean space
- fisher kernel
- svm classification
- power law
- representer theorem
- kernel pca
- kernel ridge regression
- kernel principal component analysis
- input space
- machine learning
- linear combination
- gaussian processes
- translation invariant
- normal distribution
- kernel fisher discriminant analysis
- tree kernels
- training and test data
- similarity function
- distance measure
- dimensionality reduction
- histogram intersection
- dot product
- feature vectors
- learning problems
- feature selection
- positive semi definite
- additive models
- data points
- principal component analysis
- linear svm
- probability density
- feature maps
- exponential family
- riemannian manifolds
- gaussian model