Simple and Effective: A Deterministic Auction with Support Information

We study an auction design problem where a seller aims to sell a single item to multiple bidders with independent private values. The seller knows only an upper bound on these values and does not know their distribution. The objective is to devise a deterministic auction mechanism effective across a broad set of distributions. We … Read more

Learning Optimal and Fair Policies for Online Allocation of Scarce Societal Resources from Data Collected in Deployment

We study the problem of allocating scarce societal resources of different types (e.g., permanent housing, deceased donor kidneys for transplantation, ventilators) to heterogeneous allocatees on a waitlist (e.g., people experiencing homelessness, individuals suffering from end-stage renal disease, Covid-19 patients) based on their observed covariates. We leverage administrative data collected in deployment to design an online … Read more

Distributionally Robust Linear Quadratic Control

Linear-Quadratic-Gaussian (LQG) control is a fundamental control paradigm that is studied in various fields such as engineering, computer science, economics, and neuroscience. It involves controlling a system with linear dynamics and imperfect observations, subject to additive noise, with the goal of minimizing a quadratic cost function for the state and control variables. In this work, … Read more

Distributionally Robust Optimal Allocation with Costly Verification

We consider the mechanism design problem of a principal allocating a single good to one of several agents without monetary transfers. Each agent desires the good and uses it to create value for the principal. We designate this value as the agent’s private type. Even though the principal does not know the agents’ types, she … Read more

Regret Minimization and Separation in Multi-Bidder Multi-Item Auctions

We study a robust auction design problem with a minimax regret objective, where a seller seeks a mechanism for selling multiple items to multiple bidders with additive values. The seller knows that the bidders’ values range over a box uncertainty set but has no information on their probability distribution. The robust auction design model we … Read more

Robust Multidimensional Pricing: Separation without Regret

We study a robust monopoly pricing problem with a minimax regret objective, where a seller endeavors to sell multiple goods to a single buyer, only knowing that the buyer’s values for the goods range over a rectangular uncertainty set. We interpret this pricing problem as a zero-sum game between the seller, who chooses a selling … Read more

Distributionally Robust Mechanism Design

We study a mechanism design problem where an indivisible good is auctioned to multiple bidders, for each of whom it has a private value that is unknown to the seller and the other bidders. The agents perceive the ensemble of all bidder values as a random vector governed by an ambiguous probability distribution, which belongs … Read more