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This paper introduces HACK GPs, a method that uses online learning with expert advice for kernel selection in Gaussian Processes, enhancing robustness in sequential decision-making tasks such as Bayesian optimization and active learning.
This paper proposes a cost-aware Bayesian optimization framework with level-set estimation to guide UAVs for rapid post-disaster damage assessment, reducing uncertainty while minimizing operational costs.