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cs.LG2025
From Contextual Data to Newsvendor Decisions: On the Actual Performance of Data-Driven Algorithms
Omar Besbes, Will Ma, Omar Mouchtaki
In this work, we study how the relevance/quality and quantity of past data influence performance by analyzing a contextual Newsvendor problem, in which a decision-maker trades off…
cs.LG2025
Degeneracy is OK: Logarithmic Regret for Network Revenue Management with Indiscrete Distributions
Jiashuo Jiang, Will Ma, Jiawei Zhang
We study the classical Network Revenue Management (NRM) problem with accept/reject decisions and IID arrivals. We consider a distributional form where each arrival must fall un…
cs.LG2025
Beyond IID: data-driven decision-making in heterogeneous environments
Omar Besbes, Will Ma, Omar Mouchtaki
How should one leverage historical data when past observations are not perfectly indicative of the future, e.g., due to the presence of unobserved confounders which one cannot "cor…