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This thesis explores the challenges and advancements in high-dimensional Bayesian optimization (HDBO), focusing on understanding, quantifying, and improving optimization techniques in high-dimensional spaces.Bayesian optimization (BO) is a powerful method for optimizing expensive black-box functions, but its effectiveness diminishes as the dimensionality of the search space increases due to the cu
