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Shixiang Zhu

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#machine learning Preprint Aug 2026

Deciding When to Decide: Testing Operational Suboptimality Under Distributional Shift

This work proposes \texttt{RADAR} (Regret-based Assessment of Decision Adequacy and Risk), a decision-focused framework that uses inverse optimization to infer latent preferences and tests the deployed decision's optimality gap under the current distribution.

Minxing Zheng, H. Wiberg, Shixiang Zhu · 0 citations