In this work, we aim to design a data marketplace; a robust real-time matching mechanism to
efficiently buy and sell training data for Machine Learning tasks. While the monetization of …

We present a general framework for stochastic online maximization problems with
combinatorial feasibility constraints. The framework establishes prophet inequalities by …

Bayesian persuasion studies how an informed sender should influence beliefs of rational
receivers that take decisions through Bayesian updating of a common prior. We focus on the …

Bilateral trade models the problem of intermediating between two rational agents—a seller
and a buyer—both characterized by a private valuation for an item they want to trade. We …

This survey outlines a general and modular theory for proving approximation guarantees for
equilibria of auctions in complex settings. This theory complements traditional economic …

Abstract The 2020 Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred
Nobel was awarded to Paul R. Milgrom and Robert B. Wilson for “improvements to auction …

Many real-life contractual relations differ completely from the clean, static model at the heart
of principal-agent theory. Typically, they involve repeated strategic interactions of the …

We study the problem of allocating impressions to sellers in e-commerce websites, such as
Amazon, eBay or Taobao, aiming to maximize the total revenue generated by the platform …

We analyze a scenario in which software agents implemented as regret-minimizing
algorithms engage in a repeated auction on behalf of their users. We study first-price and …

We study sequential bilateral trade where sellers and buyers valuations are completely
arbitrary ({\sl ie}, determined by an adversary). Sellers and buyers are strategic agents with …