Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets.
Aaron KleinStefan FalknerSimon BartelsPhilipp HennigFrank HutterPublished in: CoRR (2016)
Keyphrases
- hyperparameters
- machine learning
- model selection
- posterior distribution
- bayesian inference
- bayesian methods
- gaussian processes
- cross validation
- maximum likelihood
- marginal likelihood
- grid search
- parameter optimization
- closed form
- bayesian framework
- gaussian process
- random sampling
- noise level
- prior information
- support vector
- em algorithm
- machine learning algorithms
- sample size
- maximum a posteriori
- parameter estimation
- generative model
- support vector machine
- computer vision
- incomplete data
- decision trees
- data analysis
- bayesian networks
- active learning
- probabilistic model
- learning algorithm
- data sets
- parameter settings
- prior knowledge
- higher order
- supervised learning