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Predicting click and conversion probabilities when bidding on ad exchanges is at the core of the programmatic advertising industry. Two separated lines of previous works respectively address i) the prediction of user conversion probability…

Machine Learning · Statistics 2017-07-24 Eustache Diemert , Julien Meynet , Pierre Galland , Damien Lefortier

In the realm of online advertising, advertisers partake in ad auctions to obtain advertising slots, frequently taking advantage of auto-bidding tools provided by demand-side platforms. To improve the automation of these bidding systems, we…

Machine Learning · Computer Science 2025-06-30 Hao Jiang , Yongxiang Tang , Yanxiang Zeng , Pengjia Yuan , Yanhua Cheng , Teng Sha , Xialong Liu , Peng Jiang

Fairness in advertising is a topic of particular concern motivated by theoretical and empirical observations in both the computer science and economics literature. We examine the problem of fairness in advertising for general purpose…

Computer Science and Game Theory · Computer Science 2019-08-30 Shuchi Chawla , Christina Ilvento , Meena Jagadeesan

We consider some classical optimization problems in path planning and network transport, and we introduce new auction-based algorithms for their optimal and suboptimal solution. The algorithms are based on mathematical ideas that are…

Optimization and Control · Mathematics 2022-07-21 Dimitri Bertsekas

This paper develops the theory of mechanism redesign by which an auctioneer can reoptimize an auction based on bid data collected from previous iterations of the auction on bidders from the same market. We give a direct method for…

Computer Science and Game Theory · Computer Science 2022-02-15 Shuchi Chawla , Jason D. Hartline , Denis Nekipelov , Anant Shah

Today, billions of display ad impressions are purchased on a daily basis through a public auction hosted by real time bidding (RTB) exchanges. A decision has to be made for advertisers to submit a bid for each selected RTB ad request in…

Computer Science and Game Theory · Computer Science 2013-05-15 Kuang-Chih Lee , Ali Jalali , Ali Dasdan

Auto-bidding is central to computational advertising, achieving notable commercial success by optimizing advertisers' bids within economic constraints. Recently, large generative models show potential to revolutionize auto-bidding by…

Computer Science and Game Theory · Computer Science 2025-09-04 Yewen Li , Jingtong Gao , Nan Jiang , Shuai Mao , Ruyi An , Fei Pan , Xiangyu Zhao , Bo An , Qingpeng Cai , Peng Jiang

Bidding and acceptance strategies have a substantial impact on the outcome of negotiations in scenarios with linear additive and nonlinear utility functions. Over the years, it has become clear that there is no single best strategy for all…

Multiagent Systems · Computer Science 2020-09-15 Bram M. Renting , Holger H. Hoos , Catholijn M. Jonker

E-commerce platforms usually present an ordered list, mixed with several organic items and an advertisement, in response to each user's page view request. This list, the outcome of ad auction and allocation processes, directly impacts the…

Computer Science and Game Theory · Computer Science 2024-04-12 Xuejian Li , Ze Wang , Bingqi Zhu , Fei He , Yongkang Wang , Xingxing Wang

Critical sectors of human society are progressing toward the adoption of powerful artificial intelligence (AI) agents, which are trained individually on behalf of self-interested principals but deployed in a shared environment. Short of…

Multiagent Systems · Computer Science 2021-12-22 Jiachen Yang , Ethan Wang , Rakshit Trivedi , Tuo Zhao , Hongyuan Zha

When online sellers use AI learning algorithms to automatically compete on e-commerce platforms, there is concern that they will learn to coordinate on higher than competitive prices. However, this concern was primarily raised in…

General Economics · Economics 2025-11-03 Hangcheng Zhao , Ron Berman

In sponsored search advertising, advertisers need to make a series of keyword decisions. Among them, how to group these keywords to form several adgroups within a campaign is a challenging task, due to the highly uncertain environment of…

Artificial Intelligence · Computer Science 2022-03-07 Huiran Li , Yanwu Yang

We study how standard auction objectives in sponsored search markets change with refinements in the prediction of the relevance (click-through rates) of ads. We study mechanisms that optimize for a convex combination of efficiency and…

Computer Science and Game Theory · Computer Science 2013-02-28 Mukund Sundararajan , Inbal Talgam-Cohen

Internet advertising is a sophisticated game in which the many advertisers "play" to optimize their return on investment. There are many "targets" for the advertisements, and each "target" has a collection of games with a potentially…

Computational Complexity · Computer Science 2015-03-13 Bhaskar DasGupta , S. Muthukrishnan

Modern content platforms offer paid promotion to mitigate cold start by allocating exposure via auctions. Our empirical analysis reveals a counterintuitive flaw in this paradigm: while promotion rescues low-to-medium quality content, it can…

Computer Science and Game Theory · Computer Science 2026-01-29 Yumou Liu , Zhenzhe Zheng , Jiang Rong , Yao Hu , Fan Wu , Guihai Chen

Small operators who take part in secondary wireless spectrum markets typically have strict budget limits. In this paper, we study the bidding problem of a budget constrained operator in repeated secondary spectrum auctions. In existing…

Networking and Internet Architecture · Computer Science 2016-08-29 Mehrdad Khaledi , Alhussein Abouzeid

Unexpected advertising items in sponsored search may reduce users' reliance on organic search, resulting in hidden cost for the e-commerce platform. To address this problem and promote sustainable growth, we propose a dynamic reserve price…

Computer Science and Game Theory · Computer Science 2025-08-26 Mang Li

First-price auctions have very recently swept the online advertising industry, replacing second-price auctions as the predominant auction mechanism on many platforms. This shift has brought forth important challenges for a bidder: how…

Machine Learning · Computer Science 2025-09-26 Yanjun Han , Zhengyuan Zhou , Aaron Flores , Erik Ordentlich , Tsachy Weissman

The framework of budget-feasible mechanism design studies procurement auctions where the auctioneer (buyer) aims to maximize his valuation function subject to a hard budget constraint. We study the problem of designing truthful mechanisms…

Computer Science and Game Theory · Computer Science 2019-05-07 Georgios Amanatidis , Pieter Kleer , Guido Schäfer

We study mechanism design when agents may have hidden secondary goals which will manifest as non-trivial preferences among outcomes for which their primary utility is the same. We show that in such cases, a mechanism is robust against…

Computer Science and Game Theory · Computer Science 2023-07-25 Renato Paes Leme , Jon Schneider , Hanrui Zhang
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