Sufficient Decision Proxies for Decision-Focused Learning

The paper explores when different decision proxies are appropriate for decision‑focused learning (DFL) in optimization problems with uncertainty. It identifies problem properties that justify using a particular proxy and proposes alternative proxies that maintain learning complexity. Experiments on continuous, discrete, and objective‑ or constraint‑uncertain problems demonstrate the effectiveness of these approaches.

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