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Title: Statistical Limit Theorems in Distributionally Robust Optimization
The goal of this paper is to develop a methodology for the systematic analysis of asymptotic statistical properties of data-driven DRO formulations based on their corresponding non-DRO counterparts. We illustrate our approach in various settings, including both phidivergence and Wasserstein uncertainty sets. Different types of asymptotic behaviors are obtained depending on the rate at which the uncertainty radius decreases to zero as a function of the sample size and the geometry of the uncertainty sets.  more » « less
Award ID(s):
1915967 2118199
NSF-PAR ID:
10483211
Author(s) / Creator(s):
;
Publisher / Repository:
arxiv
Date Published:
Journal Name:
arXivorg
ISSN:
2331-8422
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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