Bayesian optimization

It is a method used for the global optimization of functions that are expensive to evaluate. This sequential design strategy does not assume any functional forms, making it ideal for black-box functions. It's often used in machine learning to tune hyperparameters of models, where evaluations of the function can be costly in terms of computational resources.