Rui-Ting Zuo

Optimize-via-Estimate: How to Make Finite-Sample Corrections for Sampling Uncertainty in Data-Driven Optimization

We propose a novel procedure for correcting for the effects of sampling and parameter uncertainty in data-driven convex optimization. We consider the data-driven setting wherein the distribution lies in a parametric family with unknown parameter. The decision-maker possesses a historical data set, from which solves a p...