When Wasserstein DRO Reduces Exactly: Complete Characterization, Projection Equivalence, and Regularization
Wasserstein distributionally robust optimization (DRO), a leading paradigm in data-driven decision-making, entails the evaluation of worst-case risk over a high-dimensional Wasserstein ball–a major computational burden. In this paper, we study when the worst-case risk problem admits an exact reduction to the evaluation of risk over a one-dimensional projected Wasserstein ball—a property we refer to as … Read more