Web Reference: Jul 23, 2025 · This article delves into the core concepts, working mechanisms, advantages, and applications of Bayesian Optimization, providing a comprehensive understanding of why it has become a go-to tool for optimizing complex functions. mization: Bayesian optimization. This method is particularly useful when the function to be optimized is expensive to evaluate, and we have n. information about its gradient. Bayesian optimization is a heuristic approach that is applicable to low-d. This criterion balances exploration while optimizing the function efficiently by maximizing the expected improvement. Because of the usefulness and profound impact of this principle, Jonas Mockus is widely regarded as the founder of Bayesian optimization.
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