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We study the problem of auction design for advertising platforms that face strategic advertisers who are bidding across platforms. Each advertiser's goal is to maximize their total value or conversions while satisfying some constraint(s)…

Computer Science and Game Theory · Computer Science 2024-05-07 Gagan Aggarwal , Andres Perlroth , Ariel Schvartzman , Mingfei Zhao

As commerce shifts to digital marketplaces, platforms increasingly monetize traffic through Sponsored Shopping auctions. Unlike classic ``Sponsored Search", where an advertiser typically bids for a single link, these settings involve…

Computer Science and Game Theory · Computer Science 2026-02-27 Paul Dütting , Yuhao Li , Renato Paes Leme , Kelly Spendlove , Yifeng Teng

Online bidding serves as a fundamental information system in mobile ecosystems, facilitating real-time ad allocation across billions of devices while optimizing both platform performance and user experience through data-driven decision…

Computer Science and Game Theory · Computer Science 2026-01-07 Huanyu Yan , Yu Huo , Min Lu , Weitong Ou , Xingyan Shi , Ruihe Shi , Xiaoying Tang

Advertisement (abbreviated ad) options are a recent development in online advertising. Simply, an ad option is a first look contract in which a publisher or search engine grants an advertiser a right but not obligation to enter into…

Computer Science and Game Theory · Computer Science 2015-12-11 Bowei Chen , Jun Wang

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

We study online resource allocation under non-stationary demand with a minimum offline data requirement. In this problem, a decision-maker must allocate multiple types of resources to sequentially arriving queries over a finite horizon.…

Machine Learning · Computer Science 2026-02-23 Yiding Feng , Jiashuo Jiang , Yige Wang

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 the problem of an online advertising system that wants to optimally spend an advertiser's given budget for a campaign across multiple platforms, without knowing the value for showing an ad to the users on those platforms. We model…

Computer Science and Game Theory · Computer Science 2021-03-26 Vashist Avadhanula , Riccardo Colini-Baldeschi , Stefano Leonardi , Karthik Abinav Sankararaman , Okke Schrijvers

One of the important yet insufficiently studied subjects in fair allocation is the externality effect among agents. For a resource allocation problem, externalities imply that a bundle allocated to an agent may affect the utilities of other…

Computer Science and Game Theory · Computer Science 2018-05-17 Mohammad Ghodsi , Hamed Saleh , Masoud Seddighin

We study the budget allocation problem in online marketing campaigns that utilize previously collected offline data. We first discuss the long-term effect of optimizing marketing budget allocation decisions in the offline setting. To…

Machine Learning · Computer Science 2023-09-07 Tianchi Cai , Jiyan Jiang , Wenpeng Zhang , Shiji Zhou , Xierui Song , Li Yu , Lihong Gu , Xiaodong Zeng , Jinjie Gu , Guannan Zhang

In the present work, we study the advertising competition of several marketing campaigns who need to determine how many resources to allocate to potential customers to advertise their products through direct marketing while taking into…

Computer Science and Game Theory · Computer Science 2016-08-10 Antonia Masucci , Alonso Silva

For online resource allocation problems, we propose a new demand arrival model where the sequence of arrivals contains both an adversarial component and a stochastic one. Our model requires no demand forecasting; however, due to the…

Data Structures and Algorithms · Computer Science 2018-10-02 Dawsen Hwang , Patrick Jaillet , Vahideh Manshadi

We consider a novel pricing and advertising framework, where a seller not only sets product price but also designs flexible 'advertising schemes' to influence customers' valuation of the product. We impose no structural restriction on the…

Computer Science and Game Theory · Computer Science 2024-12-12 Shipra Agrawal , Yiding Feng , Wei Tang

Online A/B testing, the gold standard for evaluating new advertising policies, consumes substantial engineering resources and risks significant revenue loss from deploying underperforming variations. This motivates the use of Off-Policy…

Machine Learning · Computer Science 2025-12-04 Hongseon Yeom , Jaeyoul Shin , Soojin Min , Jeongmin Yoon , Seunghak Yu , Dongyeop Kang

Institutions and investors face the constant challenge of making accurate decisions and predictions regarding how best they should distribute their endowments. The problem of achieving an optimal outcome at minimal cost has been extensively…

Multiagent Systems · Computer Science 2021-02-09 Theodor Cimpeanu , Cedric Perret , The Anh Han

Recent work has addressed the algorithmic problem of allocating advertisement space for keywords in sponsored search auctions so as to maximize revenue, most of which assume that pricing is done via a first-price auction. This does not…

Data Structures and Algorithms · Computer Science 2008-09-12 Yossi Azar , Benjamin Birnbaum , Anna R. Karlin , C. Thach Nguyen

We study the problem of minimizing regret in multi-mode advertisement settings, where an influence provider allocates advertising resources such as social network seeds and billboard slots to multiple advertisers with specified influence…

Computer Science and Game Theory · Computer Science 2025-11-27 Dildar Ali , Suman Benerjee , Yamuna Prasad

Real-time bidding, as one of the most popular mechanisms for selling online ad slots, facilitates advertisers to reach their potential customers. The goal of bidding optimization is to maximize the advertisers' return on investment (ROI)…

Computer Science and Game Theory · Computer Science 2019-03-01 Manxing Du , Alexander I. Cowen-Rivers , Ying Wen , Phu Sakulwongtana , Jun Wang , Mats Brorsson , Radu State

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

We present a unified framework for designing and analyzing algorithms for online budgeted allocation problems (including online matching) and their generalization, the Online Generalized Assignment Problem (OnGAP). These problems have been…

Data Structures and Algorithms · Computer Science 2013-08-27 Rad Niazadeh , Robert D. Kleinberg
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