Theoretical Analysis of Bayesian Optimisation with Unknown Gaussian Process Hyper-Parameters.
Ziyu WangNando de FreitasPublished in: CoRR (2014)
Keyphrases
- gaussian process
- hyperparameters
- posterior distribution
- bayesian inference
- gaussian processes
- model selection
- cross validation
- marginal likelihood
- maximum likelihood
- bayesian methods
- bayesian framework
- closed form
- conjugate priors
- prior information
- variational bayes
- random sampling
- em algorithm
- support vector
- maximum a posteriori
- bayesian learning
- sample size
- noise level
- incremental learning
- incomplete data
- probabilistic model
- markov chain monte carlo
- approximate inference
- posterior probability
- parameter space
- parameter estimation
- bayesian networks
- data sets
- active learning
- probability distribution
- graphical models
- expectation maximization
- latent variables
- missing values