Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters.
Marius LindauerMatthias FeurerKatharina EggenspergerAndré BiedenkappFrank HutterPublished in: CoRR (2019)
Keyphrases
- hyperparameters
- posterior distribution
- bayesian inference
- model selection
- maximum likelihood
- bayesian methods
- parameter optimization
- bayesian framework
- gaussian processes
- grid search
- cross validation
- closed form
- marginal likelihood
- prior information
- random sampling
- support vector
- gaussian process
- conjugate priors
- incremental learning
- latent variables
- maximum a posteriori
- em algorithm
- noise level
- sample size
- probabilistic model
- posterior probability
- decision trees