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- Bayesian_optimization abstract "Bayesian optimization is a sequential design strategyfor global optimization of black-box functions. Since the objective function is unknown, the Bayesian strategy is to treat it as a random function and place a prior over it.The prior captures our beliefs about the behaviour of the function.After gathering the function evaluations, which are treated as data, the prior is updatedto form the posterior distribution over the objective function.The posterior distribution, in turn, is used to constructan acquisition function that determines what the next query point should be.Examples of acquisition functions include probability of improvement,expected improvement, Bayesian expected losses, upper confidence bounds (UCB), Thompson samplingand mixtures of these. They all trade-off exploration and exploitation so as to minimize the number of function queries. As such, Bayesian optimization is well suited for functions that are very expensive to evaluate.The maximum of the acquisition function is typically found by resorting to discretization or by means of an auxiliary optimizer.The approach has been applied to solve a wide range of problems, including learning to rank, interactive animation, robotics, sensor networks, automatic algorithm configuration, automatic machine learning toolboxes, reinforcement learning, planning, visual attention, architecture configuration in deep learning, etc.The term is generally attributed to Jonas Mockus and is coined in his work from a series of publications on global optimization in the 1970s and 1980s.".
- Bayesian_optimization wikiPageExternalLink bayesianoptimization.org.
- Bayesian_optimization wikiPageExternalLink spearmint.
- Bayesian_optimization wikiPageExternalLink hyperopt.
- Bayesian_optimization wikiPageExternalLink html.
- Bayesian_optimization wikiPageID "40973765".
- Bayesian_optimization wikiPageRevisionID "595856294".
- Bayesian_optimization subject Category:Machine_learning.
- Bayesian_optimization subject Category:Sequential_experiments.
- Bayesian_optimization subject Category:Sequential_methods.
- Bayesian_optimization subject Category:Stochastic_optimization.
- Bayesian_optimization comment "Bayesian optimization is a sequential design strategyfor global optimization of black-box functions.".
- Bayesian_optimization label "Bayesian optimization".
- Bayesian_optimization sameAs m.0ywxl88.
- Bayesian_optimization sameAs Q17002908.
- Bayesian_optimization sameAs Q17002908.
- Bayesian_optimization wasDerivedFrom Bayesian_optimization?oldid=595856294.
- Bayesian_optimization isPrimaryTopicOf Bayesian_optimization.