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pojęcia
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Probability of Improvement (PI)

Acquisition function that selects the point with the highest probability of exceeding a certain improvement threshold, primarily favoring the exploitation of known areas.

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Hyperparameter of noise

Parameter of the Gaussian process that models the variance of noise in the objective function observations, essential for handling noisy data.

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Kernel

Function defining the covariance between two points in a Gaussian process, determining the regularity and properties of the modeled function (e.g., RBF kernel, Matérn).

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Regret

Performance measure in Bayesian optimization, quantifying the difference between the value of the global optimum and the best value found so far.

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Maximization of the Expected A Posteriori (MAP)

Phase of Bayesian optimization where the point that maximizes the acquisition function is found, often performed using multi-start optimization methods or grid search.

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Mutual Information Entropy

Advanced acquisition function that selects the point maximizing the expected reduction in entropy regarding the location of the global optimum, favoring highly targeted exploration.

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GP-UCB

Variant of the upper confidence bound specifically derived for Gaussian processes, with theoretical guarantees on cumulative regret.

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Multi-objective Bayesian Optimization

Extension of Bayesian optimization to problems with multiple conflicting objectives, using adapted acquisition functions such as Expected Hypervolume Improvement.

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