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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…
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…
Exterior-point Optimization for Sparse and Low-rank Optimization
Shuvomoy Das Gupta, Bartolomeo Stellato, Bart P. G. Van Parys
Many problems of substantial current interest in machine learning, statistics, and data science can be formulated as sparse and low-rank optimization problems. In this paper, we pr…