Work While They Sleep: Exploiting Evaluation Latency for Fully Bayesian Optimization
arXiv:2610.08969v2 Announce Type: replace-cross Abstract: Black-box optimization problems are ubiquitous across science and engineering, often dealing with expensive objective functions. This objective latency has two consequences during optimization: (i) the objective evaluation dominates execution time, and (ii) sample-efficient algorithms are crucial to accelerate development and avoid wasting resources. Bayesian optimization (BO) methods are the \textit{de facto} choice of planners for sugg…