A practical use of regularization for supervised learning with kernel methods.
Marco PratoLuca ZanniPublished in: Pattern Recognit. Lett. (2013)
Keyphrases
- kernel methods
- supervised learning
- learning problems
- reproducing kernel hilbert space
- kernel ridge regression
- learning tasks
- kernel matrices
- machine learning
- kernel function
- kernel matrix
- support vector
- feature space
- reproducing kernel
- support vector machine
- unsupervised learning
- training data
- multiple kernel learning
- kernel pca
- real world
- learning algorithm
- graph kernels
- training set
- reinforcement learning
- kernel machines
- kernel trick
- tikhonov regularization
- rademacher complexity
- active learning
- semi supervised
- neural network
- multiple kernel
- positive definite
- feature selection
- gaussian process
- generalization error
- transfer learning