Optimize-via-Predict: Realizing out-of-sample optimality in data-driven optimization

no code implementations • 20 Sep 2023 • Gar Goei Loke, Taozeng Zhu, Ruiting Zuo

We examine a stochastic formulation for data-driven optimization wherein the decision-maker is not privy to the true distribution, but has knowledge that it lies in some hypothesis set and possesses a historical data set, from which information about it can be gleaned.

Bayesian Optimization