6 papers
Fast Revenue Maximization
Achraf Bahamou, Omar Besbes, Omar Mouchtaki
Problem definition: We study a data-driven pricing problem in which a seller sets a price for a single item based on demand observed at a limited number of historical prices. Our g…
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…
Battery Operations in Electricity Markets: Strategic Behavior and Distortions
Jerry Anunrojwong, Santiago R. Balseiro, Omar Besbes +1
Battery storage can reduce electricity generation costs by shifting energy across time, but as privately owned batteries become large, they may also be able to exert market power.…
Robust Auction Design with Support Information
Jerry Anunrojwong, Santiago R. Balseiro, Omar Besbes
A seller wants to sell an item to buyers. Buyer valuations are drawn i.i.d. from a distribution unknown to the seller; the seller only knows that the support is included in $[a…
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…
On the Robustness of Second-Price Auctions in Prior-Independent Mechanism Design
Jerry Anunrojwong, Santiago R. Balseiro, Omar Besbes
Classical Bayesian mechanism design relies on the common prior assumption, but such prior is often not available in practice. We study the design of prior-independent mechanisms th…