Bayesian Optimization of Function Networks with Partial Evaluations

arXiv:2311.02146v2 Announce Type: replace-cross
Abstract: Bayesian optimization is a powerful framework for optimizing functions that are expensive or time-consuming to evaluate. Recent work has considered Bayesian optimization of function networks (BOFN), where the objective function is given by a network of functions, each taking as input the output of previous nodes in the network as well as additional parameters. Leveraging this network structure has been shown to yield significant performance improvements. Existing BOFN algorithms for general-purpose networks evaluate the full …

abstract arxiv bayesian cs.lg framework function functions input math.oc network networks nodes optimization output replace stat.ml type work