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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 second-price auctions, as well as their generalized versions (e.g.,…

Computer Science and Game Theory · Computer Science 2022-03-28 Yoav Kolumbus , Noam Nisan

We design mechanisms for online procurement of data held by strategic agents for machine learning tasks. The challenge is to use past data to actively price future data and give learning guarantees even when an agent's cost for revealing…

Computer Science and Game Theory · Computer Science 2015-06-09 Jacob Abernethy , Yiling Chen , Chien-Ju Ho , Bo Waggoner

Learning to bid in repeated first-price auctions is a fundamental problem at the interface of game theory and machine learning, which has seen a recent surge in interest due to the transition of display advertising to first-price auctions.…

Computer Science and Game Theory · Computer Science 2024-07-09 Rachitesh Kumar , Jon Schneider , Balasubramanian Sivan

The standard framework of online bidding algorithm design assumes that the seller commits himself to faithfully implementing the rules of the adopted auction. However, the seller may attempt to cheat in execution to increase his revenue if…

Computer Science and Game Theory · Computer Science 2023-11-28 Qian Wang , Xuanzhi Xia , Zongjun Yang , Xiaotie Deng , Yuqing Kong , Zhilin Zhang , Liang Wang , Chuan Yu , Jian Xu , Bo Zheng

Learning effective pricing strategies is crucial in digital marketplaces, especially when buyers' valuations are unknown and must be inferred through interaction. We study the online contextual pricing problem, where a seller observes a…

Computer Science and Game Theory · Computer Science 2026-02-18 Joon Suk Huh , Kirthevasan Kandasamy

The creator economy has revolutionized the way individuals can profit through online platforms. In this paper, we initiate the study of online learning in the creator economy by modeling the creator economy as a three-party game between the…

Computer Science and Game Theory · Computer Science 2023-05-22 Banghua Zhu , Sai Praneeth Karimireddy , Jiantao Jiao , Michael I. Jordan

First-price auctions have largely replaced traditional bidding approaches based on Vickrey auctions in programmatic advertising. As far as learning is concerned, first-price auctions are more challenging because the optimal bidding strategy…

Machine Learning · Computer Science 2021-11-23 Juliette Achddou , Olivier Cappé , Aurélien Garivier

Contextual pricing strategies are prevalent in online retailing, where the seller adjusts prices based on products' attributes and buyers' characteristics. Although such strategies can enhance seller's profits, they raise concerns about…

Computer Science and Game Theory · Computer Science 2026-03-17 Pangpang Liu , Will Wei Sun

We consider a multi-round auction setting motivated by pay-per-click auctions for Internet advertising. In each round the auctioneer selects an advertiser and shows her ad, which is then either clicked or not. An advertiser derives value…

Data Structures and Algorithms · Computer Science 2013-06-05 Moshe Babaioff , Yogeshwer Sharma , Aleksandrs Slivkins

We study the dynamic pricing problem with knapsack, addressing the challenge of balancing exploration and exploitation under resource constraints. We introduce three algorithms tailored to different informational settings: a Boundary…

Optimization and Control · Mathematics 2025-01-27 Ruicheng Ao , Jiashuo Jiang , David Simchi-Levi

With the advent and increasing consolidation of e-commerce, digital advertising has very recently replaced traditional advertising as the main marketing force in the economy. In the past four years, a particularly important development in…

Computer Science and Game Theory · Computer Science 2022-11-14 Wei Zhang , Yanjun Han , Zhengyuan Zhou , Aaron Flores , Tsachy Weissman

We propose a new partial-observability model for online learning problems where the learner, besides its own loss, also observes some noisy feedback about the other actions, depending on the underlying structure of the problem. We represent…

Machine Learning · Computer Science 2026-04-16 Tomáš Kocák , Gergely Neu , Michal Valko

In an online contract selection problem there is a seller which offers a set of contracts to sequentially arriving buyers whose types are drawn from an unknown distribution. If there exists a profitable contract for the buyer in the offered…

Machine Learning · Computer Science 2013-05-16 Cem Tekin , Mingyan Liu

We study an online learning problem on dynamic pricing and resource allocation, where we make joint pricing and inventory decisions to maximize the overall net profit. We consider the stochastic dependence of demands on the price, which…

Machine Learning · Computer Science 2025-05-23 Jianyu Xu , Xuan Wang , Yu-Xiang Wang , Jiashuo Jiang

We study a game between autobidding algorithms that compete in an online advertising platform. Each autobidder is tasked with maximizing its advertiser's total value over multiple rounds of a repeated auction, subject to budget and…

Computer Science and Game Theory · Computer Science 2024-12-03 Brendan Lucier , Sarath Pattathil , Aleksandrs Slivkins , Mengxiao Zhang

We consider the problem of a single seller repeatedly selling a single item to a single buyer (specifically, the buyer has a value drawn fresh from known distribution $D$ in every round). Prior work assumes that the buyer is fully rational…

Computer Science and Game Theory · Computer Science 2017-11-28 Mark Braverman , Jieming Mao , Jon Schneider , S. Matthew Weinberg

This paper proposes a theoretical analysis of recommendation systems in an online setting, where items are sequentially recommended to users over time. In each round, a user, randomly picked from a population of $m$ users, requests a…

Machine Learning · Statistics 2020-10-26 Kaito Ariu , Narae Ryu , Se-Young Yun , Alexandre Proutière

Bilateral trade is one of the most natural and important forms of economic interaction: A seller has a single, indivisible item for sale, and a buyer is potentially interested. The two parties typically have different, privately known…

Computer Science and Game Theory · Computer Science 2023-12-20 Yixuan Even Xu , Hanrui Zhang , Vincent Conitzer

Online advertising has recently grown into a highly competitive and complex multi-billion-dollar industry, with advertisers bidding for ad slots at large scales and high frequencies. This has resulted in a growing need for efficient…

Machine Learning · Computer Science 2023-07-04 Zhe Feng , Swati Padmanabhan , Di Wang

We consider the problem of a firm seeking to use personalized pricing to sell an exogenously given stock of a product over a finite selling horizon to different consumer types. We assume that the type of an arriving consumer can be observed…

Machine Learning · Computer Science 2021-10-08 Ningyuan Chen , Guillermo Gallego
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