Scalable Gaussian Process Hyperparameter Optimization via Coverage Regularization.
Killian WoodAlec M. DuntonAmanda MuyskensBenjamin W. PriestPublished in: CoRR (2022)
Keyphrases
- gaussian process
- gaussian processes
- reproducing kernel hilbert space
- regression model
- hyperparameters
- sparse approximation
- grid search
- model selection
- gaussian process regression
- latent variables
- approximate inference
- bayesian framework
- semi supervised
- gaussian process models
- expectation propagation
- gaussian process classification
- bayesian inference
- prior information
- kernel machines
- cross validation
- covariance function
- sparse approximations
- machine learning
- parameter settings
- higher order
- marginal likelihood
- denoising
- probabilistic model
- pairwise