“…By contrast, in regression, we only observe a single scalar response for the chosen set of features, thus creating correlations. Another recent work by Defourny et al (2015) has considered semidefinite programming (SDP) relaxations for VIPs, but assumes known sampling noise as well as a continuous decision space. Finally, one stream of research (Norkin et al 1998, Xu andNelson 2013) applies branch-and-bound techniques to discrete simulation optimization, but treats the objective function as a black box, without the additional parametric structure afforded by regression.…”