Kernel Pre-Training in Feature Space via m-Kernels.
Alistair ShiltonSunil GuptaSantu RanaPratibha VellankiCheng LiSvetha VenkateshLaurence ParkAlessandra SuttiDavid RubinThomas DorinAlireza VahidMurray HeightTeo SlezakPublished in: CoRR (2018)
Keyphrases
- feature space
- kernel function
- kernel methods
- training samples
- training set
- input space
- dot product
- polynomial kernels
- gaussian kernels
- high dimensional feature space
- kernel matrix
- positive definite
- feature vectors
- optimal kernel
- feature selection
- kernel trick
- classification accuracy
- data points
- linear svm
- support vector
- high dimensional
- feature extraction
- kernel learning
- principal component analysis
- hyperplane
- rbf kernel
- support vector machine
- kernel machines
- kernel matrices
- image representation
- riemannian manifolds
- kernel pca
- reproducing kernel hilbert space
- multiple kernel learning
- svm classifier
- linear combination
- low dimensional
- linear discriminant analysis
- similarity measure
- class separability
- training process
- histogram intersection
- positive semidefinite
- mercer kernels
- multiple kernel
- kernel parameters
- kernel principal component analysis
- svm classification
- support vectors
- similarity function
- feature set