Sparse Gaussian Process Hyperparameters: Optimize or Integrate?
Vidhi LalchandWessel P. BruinsmaDavid R. BurtCarl E. RasmussenPublished in: CoRR (2022)
Keyphrases
- gaussian process
- hyperparameters
- covariance function
- model selection
- gaussian processes
- cross validation
- bayesian framework
- closed form
- gaussian process regression
- bayesian inference
- support vector
- random sampling
- prior information
- sample size
- em algorithm
- noise level
- posterior distribution
- approximate inference
- maximum a posteriori
- maximum likelihood
- incomplete data
- variational bayes
- incremental learning
- regression model
- expectation propagation
- parameter space
- non stationary
- grid search
- prior knowledge
- high dimensional
- missing values
- semi supervised
- active learning
- pairwise
- bayesian methods
- data sets
- parameter settings
- genetic algorithm ga
- parameter estimation
- generative model
- probabilistic model
- bayesian networks
- learning algorithm