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Most of the work in the auction design literature assumes that bidders behave rationally based on the information available for every individual auction, and the revelation principle enables designers to restrict their efforts to incentive…

Computer Science and Game Theory · Computer Science 2024-05-14 Juncheng Li , Pingzhong Tang

Randomized experiments in which the treatment of a unit can affect the outcomes of other units are becoming increasingly common in healthcare, economics, and in the social and information sciences. From a causal inference perspective, the…

Methodology · Statistics 2017-02-14 Daniel L. Sussman , Edoardo M. Airoldi

We design online algorithms for the fair allocation of public goods to a set of $N$ agents over a sequence of $T$ rounds and focus on improving their performance using predictions. In the basic model, a public good arrives in each round,…

Computer Science and Game Theory · Computer Science 2022-10-03 Siddhartha Banerjee , Vasilis Gkatzelis , Safwan Hossain , Billy Jin , Evi Micha , Nisarg Shah

This paper presents models for predicted click-through rates in position auctions that take into account two possibilities that are not normally considered---that the identities of ads shown in other positions may affect the probability…

Computer Science and Game Theory · Computer Science 2014-09-17 Patrick Hummel , R. Preston McAfee

Auto-bidding systems are widely used in advertising to automatically determine bid values under constraints such as total budget and Return-on-Spend (RoS) targets. Existing works often assume that the value of an ad impression, such as the…

Machine Learning · Computer Science 2026-02-03 Jiale Han , Chun Gan , Chengcheng Zhang , Jie He , Zhangang Lin , Ching Law , Xiaowu Dai

Online auctions are one of the most fundamental facets of the modern economy and power an industry generating hundreds of billions of dollars a year in revenue. Auction theory has historically focused on the question of designing the best…

Computer Science and Game Theory · Computer Science 2021-09-23 Thomas Nedelec , Clément Calauzènes , Noureddine El Karoui , Vianney Perchet

In this paper, we consider the problem of optimizing the revenue a web publisher gets through real-time bidding (i.e. from ads sold in real-time auctions) and direct (i.e. from ads sold through contracts agreed in advance). We consider a…

Computer Science and Game Theory · Computer Science 2020-06-15 Grégoire Jauvion , Nicolas Grislain

We examine two types of binary betting markets, whose primary goal is for profit (such as sports gambling) or to gain information (such as prediction markets). We articulate the interplay between belief and price-setting to analyse both…

Computer Science and Game Theory · Computer Science 2024-06-07 Haiqing Zhu , Alexander Soen , Yun Kuen Cheung , Lexing Xie

The majority of online display ads are served through real-time bidding (RTB) --- each ad display impression is auctioned off in real-time when it is just being generated from a user visit. To place an ad automatically and optimally, it is…

Machine Learning · Computer Science 2017-01-13 Han Cai , Kan Ren , Weinan Zhang , Kleanthis Malialis , Jun Wang , Yong Yu , Defeng Guo

The online advertising market, with its thousands of auctions run per second, presents a daunting challenge for advertisers who wish to optimize their spend under a budget constraint. Thus, advertising platforms typically provide automated…

Machine Learning · Computer Science 2023-10-17 Dmytro Korenkevych , Frank Cheng , Artsiom Balakir , Alex Nikulkov , Lingnan Gao , Zhihao Cen , Zuobing Xu , Zheqing Zhu

This paper studies the measurement of advertising effects on online platforms when parallel experimentation occurs, that is, when multiple advertisers experiment concurrently. It provides a framework that makes precise how parallel…

General Economics · Economics 2024-03-01 Caio Waisman , Navdeep S. Sahni , Harikesh S. Nair , Xiliang Lin

In online internet advertising, machine learning models are widely used to compute the likelihood of a user engaging with product related advertisements. However, the performance of traditional machine learning models is often impacted due…

Information Retrieval · Computer Science 2018-06-22 Marcelo Tallis , Pranjul Yadav

Online advertising is progressively moving towards a programmatic model in which ads are matched to actual interests of individuals collected as they browse the web. Letting the huge debate around privacy aside, a very important question in…

Computer Science and Game Theory · Computer Science 2017-09-26 Panagiotis Papadopoulos , Nicolas Kourtellis , Pablo Rodriguez Rodriguez , Nikolaos Laoutaris

Today's online advertisers procure digital ad impressions through interacting with autobidding platforms: advertisers convey high level procurement goals via setting levers such as budget, target return-on-investment, max cost per click,…

Information Retrieval · Computer Science 2023-07-13 Jason Cheuk Nam Liang , Haihao Lu , Baoyu Zhou

Internet search companies sell advertisement slots based on users' search queries via an auction. Advertisers have to determine how to place bids on the keywords of their interest in order to maximize their return for a given budget: this…

Data Structures and Algorithms · Computer Science 2007-09-24 S. Muthukrishnan , Martin Pal , Zoya Svitkina

The real-time bidding (RTB), aka programmatic buying, has recently become the fastest growing area in online advertising. Instead of bulking buying and inventory-centric buying, RTB mimics stock exchanges and utilises computer algorithms to…

Computer Science and Game Theory · Computer Science 2013-06-28 Shuai Yuan , Jun Wang , Xiaoxue Zhao

Pay-per-click advertising includes various formats (\emph{e.g.}, search, contextual, social) with a total investment of more than 200 billion USD per year worldwide. An advertiser is given a daily budget to allocate over several, even…

Machine Learning · Computer Science 2020-03-04 Alessandro Nuara , Francesco Trovò , Nicola Gatti , Marcello Restelli

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

A popular approach to selling online advertising is by a waterfall, where a publisher makes sequential price offers to ad networks for an inventory, and chooses the winner in that order. The publisher picks the order and prices to maximize…

Machine Learning · Computer Science 2019-04-23 Branislav Kveton , Saied Mahdian , S. Muthukrishnan , Zheng Wen , Yikun Xian

Advertising becomes one of the most popular ways of monetizing an online transaction platform. Usually, sponsored advertisements are posted on the most attractive positions to enhance the number of clicks. However, multiple e-commerce…

Computer Science and Game Theory · Computer Science 2022-04-22 Weian Li , Qi Qi , Changjun Wang , Changyuan Yu