Preprint
Aug 2026
Achieving First-Order Statistical Improvements in Data-Driven Optimization: From No-Free-Lunch to Amplified Decision Perturbation
It is argued that without additional, correctly specified, side information, any EO+ method can result in at most second-order improvements, and a negative conclusion is provided, namely ``no free lunch is possible", on the statistical power of EO+.
Henry Lam, Tianyu Wang
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