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Conformal-DRO: Distributionally Robust Optimization with Conformalized Ambiguity Set
Data-driven distributionally robust optimization (DRO) typically treats the conditional outcome law as fixed and uses ambiguity sets to capture estimation error. This paper studies latent distributional heterogeneity, where each instance has an unobserved law but contributes only one observation, so
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