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Cost per click is a common metric to judge digital advertising campaign performance. In this paper we discuss an approach that generates a feature targeting recommendation to optimise cost per click. We also discuss a technique to assign…

Applications · Statistics 2021-08-03 Aditya Jain , Sahil Khan

The society's insatiable appetites for personal data are driving the emergency of data markets, allowing data consumers to launch customized queries over the datasets collected by a data broker from data owners. In this paper, we study how…

Computational Engineering, Finance, and Science · Computer Science 2019-12-02 Chaoyue Niu , Zhenzhe Zheng , Fan Wu , Shaojie Tang , Guihai Chen

We study a game played between advertisers in an online ad platform. The platform sells ad impressions by first-price auction and provides autobidding algorithms that optimize bids on each advertiser's behalf, subject to advertiser…

Computer Science and Game Theory · Computer Science 2023-11-16 Yiding Feng , Brendan Lucier , Aleksandrs Slivkins

We establish a general optimization framework for the design of automated bidding agent in dynamic online marketplaces. It optimizes solely for the buyer's interest and is agnostic to the auction mechanism imposed by the seller. As a…

Computer Science and Game Theory · Computer Science 2022-02-28 Yuan Gao , Kaiyu Yang , Yuanlong Chen , Min Liu , Noureddine El Karoui

Many online companies sell advertisement space in second-price auctions with reserve. In this paper, we develop a probabilistic method to learn a profitable strategy to set the reserve price. We use historical auction data with features to…

Machine Learning · Statistics 2015-06-25 Maja R. Rudolph , Joseph G. Ellis , David M. Blei

In this study, we apply reinforcement learning techniques and propose what we call reinforcement mechanism design to tackle the dynamic pricing problem in sponsored search auctions. In contrast to previous game-theoretical approaches that…

Computer Science and Game Theory · Computer Science 2017-11-29 Weiran Shen , Binghui Peng , Hanpeng Liu , Michael Zhang , Ruohan Qian , Yan Hong , Zhi Guo , Zongyao Ding , Pengjun Lu , Pingzhong Tang

In online advertising, advertisers commonly utilize auto-bidding services to bid for impression opportunities. A typical objective of the auto-bidder is to optimize the advertiser's cumulative value of winning impressions within specified…

Computer Science and Game Theory · Computer Science 2025-02-11 Zhijian Duan , Yusen Huo , Tianyu Wang , Zhilin Zhang , Yeshu Li , Chuan Yu , Jian Xu , Bo Zheng , Xiaotie Deng

Guaranteed display (GD) advertising is a critical component of advertising since it provides publishers with stable revenue and enables advertisers to target specific audiences with guaranteed impressions. However, smooth pacing control for…

Computer Science and Game Theory · Computer Science 2023-12-12 Liang Dai , Kejie Lyu , Chengcheng Zhang , Guangming Zhao , Zhonglin Zu , Liang Wang , Bo Zheng

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

Usage-based insurance (UBI) uses telematics to align premiums with risk and encourage safe driving. However, deploying these programs is challenging due to heavy-tailed claim costs, nonstationary driver behavior, and limited incentive…

Optimization and Control · Mathematics 2026-05-11 Qinyang He , Yonatan Mintz

Auctions are becoming an increasingly popular method for transacting business, especially over the Internet. This article presents a general approach to building autonomous bidding agents to bid in multiple simultaneous auctions for…

Artificial Intelligence · Computer Science 2011-06-28 J. A. Csirik , M. L. Littman , D. McAllester , R. E. Schapire , P. Stone

In the classic Adwords problem introduced by Mehta et al.\ (2007), we have a bipartite graph between advertisers and queries. Each advertiser has a maximum budget that is known a priori. Queries are unknown a priori and arrive sequentially.…

Data Structures and Algorithms · Computer Science 2024-03-29 Rajan Udwani

Online media provides opportunities for marketers through which they can deliver effective brand messages to a wide range of audiences. Advertising technology platforms enable advertisers to reach their target audience by delivering ad…

Artificial Intelligence · Computer Science 2016-01-12 Shahriar Shariat , Burkay Orten , Ali Dasdan

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

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

We present a model of digital advertising with three key features: (i) advertisers can reach consumers on and off a platform, (ii) additional data enhances the value of advertiser-consumer matches, and (iii) bidding follows auction-like…

Theoretical Economics · Economics 2024-04-25 Dirk Bergemann , Alessandro Bonatti , Nicholas Wu

In E-commerce advertising, where product recommendations and product ads are presented to users simultaneously, the traditional setting is to display ads at fixed positions. However, under such a setting, the advertising system loses the…

Machine Learning · Computer Science 2019-09-04 Weixun Wang , Junqi Jin , Jianye Hao , Chunjie Chen , Chuan Yu , Weinan Zhang , Jun Wang , Xiaotian Hao , Yixi Wang , Han Li , Jian Xu , Kun Gai

Calibration is defined as the ratio of the average predicted click rate to the true click rate. The optimization of calibration is essential to many online advertising recommendation systems because it directly affects the downstream bids…

Machine Learning · Computer Science 2023-03-22 Yewen Fan , Nian Si , Kun Zhang

The display advertising industry has recently transitioned from second- to first-price auctions as its primary mechanism for ad allocation and pricing. In light of this, publishers need to re-evaluate and optimize their auction parameters,…

Computer Science and Game Theory · Computer Science 2020-06-30 Zhe Feng , Sébastien Lahaie , Jon Schneider , Jinchao Ye

In recent years, RTB(Real Time Bidding) becomes a popular online advertisement trading method. During the auction, each DSP(Demand Side Platform) is supposed to evaluate current opportunity and respond with an ad and corresponding bid…

Machine Learning · Statistics 2017-12-29 Huahui Liu , Mingrui Zhu , Xiaonan Meng , Yi Hu , Hao Wang