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Related papers: Fair Online Bilateral Trade

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Bilateral trade models the problem of facilitating trades between a seller and a buyer having private valuations for the item being sold. In the online version of the problem, the learner faces a new seller and buyer at each time step, and…

Computer Science and Game Theory · Computer Science 2024-05-29 Solenne Gaucher , Martino Bernasconi , Matteo Castiglioni , Andrea Celli , Vianney Perchet

Bilateral trade, a fundamental topic in economics, models the problem of intermediating between two strategic agents, a seller and a buyer, willing to trade a good for which they hold private valuations. In this paper, we cast the bilateral…

Computer Science and Game Theory · Computer Science 2021-09-28 Nicolò Cesa-Bianchi , Tommaso Cesari , Roberto Colomboni , Federico Fusco , Stefano Leonardi

We investigate online pricing in two-sided markets where a platform repeatedly posts prices based on binary accept/reject feedback to maximize gains-from-trade (GFT) or profit. We characterize the regret achievable across three mechanism…

Computer Science and Game Theory · Computer Science 2026-02-13 Yiding Feng , Mengfan Ma , Bo Peng , Zongqi Wan

Bilateral trade models the task of intermediating between two strategic agents, a seller and a buyer, willing to trade a good for which they hold private valuations. We study this problem from the perspective of a broker, in a regret…

Computer Science and Game Theory · Computer Science 2025-09-29 Simone Di Gregorio , Paul Dütting , Federico Fusco , Chris Schwiegelshohn

We study repeated bilateral trade when the valuations of the sellers and the buyers are contextual. More precisely, the agents' valuations are given by the inner product of a context vector with two unknown $d$-dimensional vectors -- one…

Computer Science and Game Theory · Computer Science 2026-02-16 Romain Cosson , Federico Fusco , Anupam Gupta , Stefano Leonardi , Renato Paes Leme , Matteo Russo

Bilateral trade, a fundamental topic in economics, models the problem of intermediating between two strategic agents, a seller and a buyer, willing to trade a good for which they hold private valuations. Despite the simplicity of this…

Machine Learning · Computer Science 2024-02-20 Nicolò Cesa-Bianchi , Tommaso Cesari , Roberto Colomboni , Federico Fusco , Stefano Leonardi

We investigate brokerage between traders from an online learning perspective. At any round $t$, two traders arrive with their private valuations, and the broker proposes a trading price. Unlike other bilateral trade problems already studied…

Machine Learning · Computer Science 2023-10-19 Nataša Bolić , Tommaso Cesari , Roberto Colomboni

We study online bilateral trade, where a learner facilitates repeated exchanges between a buyer and a seller to maximize the Gain From Trade (GFT), i.e., the social welfare. In doing so, the learner must guarantee not to subsidize the…

Computer Science and Game Theory · Computer Science 2026-02-06 Anna Lunghi , Mattia Piccinato , Matteo Castiglioni , Alberto Marchesi

We study a repeated trading problem in which a mechanism designer facilitates trade between a single seller and multiple buyers. Our model generalizes the classic bilateral trade setting to a multi-buyer environment. Specifically, the…

Computer Science and Game Theory · Computer Science 2025-03-04 Anna Lunghi , Matteo Castiglioni , Alberto Marchesi

Double Auction enables decentralized transfer of goods between multiple buyers and sellers, thus underpinning functioning of many online marketplaces. Buyers and sellers compete in these markets through bidding, but do not often know their…

Machine Learning · Computer Science 2023-07-11 Soumya Basu , Abishek Sankararaman

We study sequential bilateral trade where sellers and buyers valuations are completely arbitrary (i.e., determined by an adversary). Sellers and buyers are strategic agents with private valuations for the good and the goal is to design a…

Computer Science and Game Theory · Computer Science 2024-10-11 Yossi Azar , Amos Fiat , Federico Fusco

Bilateral trade models the task of intermediating between two strategic agents, a seller and a buyer, who wish to trade a good. We study this problem from the perspective of a profit-maximizing broker within an online learning framework,…

Computer Science and Game Theory · Computer Science 2026-05-14 Simone Di Gregorio , Paul Dütting , Federico Fusco , Chris Schwiegelshohn

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 study the online learning version of the problem, in…

Computer Science and Game Theory · Computer Science 2024-09-04 Martino Bernasconi , Matteo Castiglioni , Andrea Celli , Federico Fusco

Price discrimination, which refers to the strategy of setting different prices for different customer groups, has been widely used in online retailing. Although it helps boost the collected revenue for online retailers, it might create…

Machine Learning · Computer Science 2023-07-31 Xi Chen , Jiameng Lyu , Xuan Zhang , Yuan Zhou

We study repeated bilateral trade where an adaptive $\sigma$-smooth adversary generates the valuations of sellers and buyers. We provide a complete characterization of the regret regimes for fixed-price mechanisms under different feedback…

Machine Learning · Computer Science 2024-02-20 Nicolò Cesa-Bianchi , Tommaso Cesari , Roberto Colomboni , Federico Fusco , Stefano Leonardi

We explore brokerage between traders in an online learning framework. At any round $t$, two traders meet to exchange an asset, provided the exchange is mutually beneficial. The broker proposes a trading price, and each trader tries to sell…

Computer Science and Game Theory · Computer Science 2024-05-24 Tommaso Cesari , Roberto Colomboni

We study the problem of online dynamic pricing with two types of fairness constraints: a "procedural fairness" which requires the proposed prices to be equal in expectation among different groups, and a "substantive fairness" which requires…

Machine Learning · Computer Science 2022-09-27 Jianyu Xu , Dan Qiao , Yu-Xiang Wang

In online marketplaces, customers have access to hundreds of reviews for a single product. Buyers often use reviews from other customers that share their type -- such as height for clothing, skin type for skincare products, and location for…

Computer Science and Game Theory · Computer Science 2023-09-12 Wenshuo Guo , Nika Haghtalab , Kirthevasan Kandasamy , Ellen Vitercik

Motivated by online retail, we consider the problem of selling one item (e.g., an ad slot) to two non-excludable buyers (say, a merchant and a brand). This problem captures, for example, situations where a merchant and a brand cooperatively…

Computer Science and Game Theory · Computer Science 2025-05-26 Gagan Aggarwal , Ashwinkumar Badanidiyuru , Paul Dütting , Federico Fusco

Auctions with partially-revealed information about items are broadly employed in real-world applications, but the underlying mechanisms have limited theoretical support. In this work, we study a machine learning formulation of these types…

Machine Learning · Computer Science 2022-07-06 Wenshuo Guo , Michael I. Jordan , Ellen Vitercik
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