Bayesian optimization is a sequential model-based strategy for global optimization of black-box objective functions whose evaluations are costly. It is commonly used when a single observation requires an experiment, engineering computation, numerical simulation, or machine-learning run, and when derivatives are unavailable or unreliable.
Bayesian optimization is a sequential model-based strategy for global optimization of black-box objective functions whose evaluations are costly. It is commonly used when a single observation requires an experiment, engineering computation, numerical simulation, or machine-learning run, and when derivatives are unavailable or unreliable.
Source: Wikipedia "Bayesian optimization" · CC BY-SA 4.0
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