How priors of initial hyperparameters affect Gaussian process regression models.
Zexun ChenBo WangPublished in: Neurocomputing (2018)
Keyphrases
- gaussian process
- regression model
- hyperparameters
- model selection
- bayesian framework
- gaussian processes
- covariance function
- prior information
- maximum a posteriori
- gaussian process regression
- cross validation
- marginal likelihood
- approximate inference
- bayesian inference
- variational bayes
- closed form
- posterior distribution
- support vector
- sample size
- support vector regression
- grid search
- dirichlet process
- bayesian methods
- random sampling
- markov random field
- feature selection
- noise level
- incremental learning
- latent variables
- parameter estimation
- expectation propagation
- machine learning