Optimal learning rates for least squares SVMs using Gaussian kernels.
Mona EbertsIngo SteinwartPublished in: NIPS (2011)
Keyphrases
- gaussian kernels
- least squares
- learning rate
- kernel function
- covering numbers
- gaussian kernel
- support vector
- optimal parameters
- feature space
- ls svm
- multiple kernel learning
- reproducing kernel hilbert space
- uniform convergence
- kernel methods
- optimal solution
- support vector machine
- multi class
- kernel principal component analysis
- binary classification
- learning algorithm
- support vectors
- scale space
- knn
- input space
- training data
- rbf network
- linear model
- diffusion equation
- kernel learning
- convergence rate
- upper bound
- machine learning