Just Interpolate: Kernel "Ridgeless" Regression Can Generalize.
Tengyuan LiangAlexander RakhlinPublished in: CoRR (2018)
Keyphrases
- kernel ridge regression
- reproducing kernel hilbert space
- classification and regression problems
- sparse kernel
- gaussian processes
- kernel regression
- support vector
- kernel function
- kernel methods
- regression model
- linear regression
- regression method
- gaussian process regression
- mercer kernels
- ridge regression
- support vector regression
- principal component regression
- gaussian kernels
- kernel partial least squares
- relevance vector machine
- euclidean space
- feature space
- kernel matrix
- regression problems
- machine learning
- gaussian process
- polynomial regression
- string kernels
- polynomial kernels
- covariance function
- pairwise
- loss function
- regression methods
- input space
- component analysis
- feature selection
- gradient boosting
- face recognition
- regression function
- neural network
- kernel matrices
- kernel space
- locally weighted
- support vector machine
- model selection
- cross validation
- kernel learning
- regression analysis