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math.OC2026
Harnessing Heterogeneous Data for Conditional Optimization via Optimal Transport
Jonathan Yu-Meng Li, Qinyu Wu
Conditional optimization tailors decisions to contextual or event information, but its practical use is often limited by the difficulty of learning the relevant conditional distrib…
math.OC2026
Sampler-Robust Optimization under Generative Models
Ziwei Zhang, Jonathan Yu-Meng Li
Modern stochastic optimization pipelines increasingly rely on learned generative models to represent uncertainty, while downstream decisions are evaluated almost entirely through M…
math.OC2025
Reconciling Risk-Aversion Paradoxes in the Distribution-Free Newsvendor Problem: Scarf's Rule Meets Dual Utility
Jonathan Yu-Meng Li, Tiantian Mao, Reza Valimoradi
How should a risk-averse newsvendor order optimally under distributional ambiguity? Attempts to extend Scarf's celebrated distribution-free ordering rule using risk measures have l…