1 citations · 1 across the 1 of their papers we have counts for
4 papers
Learning Decision-Focused Uncertainty Sets in Robust Optimization
Irina Wang, Bart Van Parys, Bartolomeo Stellato
We propose a data-driven technique to automatically learn contextual uncertainty sets in robust optimization, resulting in excellent worst-case and average-case performance while a…
Globalized Adversarial Regret Optimization: Robust Decisions with Uncalibrated Predictions
Jannis Kurtz, Bart P. G. van Parys
Optimization problems routinely depend on uncertain parameters that must be predicted before a decision is made. Classical robust and regret formulations are designed to handle err…
Holistic Robust Data-Driven Decisions
Amine Bennouna, Bart Van Parys, Ryan Lucas
The design of data-driven formulations for machine learning and decision-making with good out-of-sample performance is a key challenge. The observation that good in-sample performa…
From Distributional Robustness to Robust Statistics: A Confidence Sets Perspective
Gabriel Chan, Bart Van Parys, Amine Bennouna
We establish a connection between distributionally robust optimization (DRO) and classical robust statistics. We demonstrate that this connection arises naturally in the context of…