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The causal effect of showing an ad to a potential customer versus not, commonly referred to as "incrementality", is the fundamental question of advertising effectiveness. In digital advertising three major puzzle pieces are central to…

Machine Learning · Computer Science 2022-08-30 Randall Lewis , Jeffrey Wong

In today's businesses, marketing has been a central trend for growth. Marketing quality is equally important as product quality and relevant metrics. Quality of Marketing depends on targeting the right person. Technology adaptations have…

Multiagent Systems · Computer Science 2024-09-17 Afzal Ahmed , Muhammad Raees

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

In online advertising systems, publishers often face a trade-off in information disclosure strategies: while disclosing more information can enhance efficiency by enabling optimal allocation of ad impressions, it may lose revenue potential…

Computer Science and Game Theory · Computer Science 2025-04-01 Yue Yin

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

Media recommender systems aim to capture users' preferences and provide precise personalized recommendation of media content. There are two critical components in the common paradigm of modern recommender models: (1) representation…

Information Retrieval · Computer Science 2022-01-11 Yanfang Wang , Yongduo Sui , Xiang Wang , Zhenguang Liu , Xiangnan He

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

Online retailers often use third-party demand-side-platforms (DSPs) to conduct offsite advertising and reach shoppers across the Internet on behalf of their advertisers. The process involves the retailer participating in instant auctions…

Systems and Control · Electrical Eng. & Systems 2023-10-26 Hangjian Li , Dong Xu , Konstantin Shmakov , Kuang-Chih Lee , Wei Shen

In this paper, we initiate the study of the multiplicative bidding language adopted by major Internet search companies. In multiplicative bidding, the effective bid on a particular search auction is the product of a base bid and bid…

Data Structures and Algorithms · Computer Science 2014-04-29 MohammadHossein Bateni , Jon Feldman , Vahab Mirrokni , Sam Chiu-wai Wong

Budget-management systems are one of the key components of modern auction markets. Internet advertising platforms typically offer advertisers the possibility to pace the rate at which their budget is depleted, through budget-pacing…

Computer Science and Game Theory · Computer Science 2021-06-18 Andrea Celli , Riccardo Colini-Baldeschi , Christian Kroer , Eric Sodomka

Advertisers play an essential role in many e-commerce platforms like Taobao and Amazon. Fulfilling their marketing needs and supporting their business growth is critical to the long-term prosperity of platform economies. However, compared…

Machine Learning · Computer Science 2022-02-21 Qianqian Zhang , Xinru Liao , Quan Liu , Jian Xu , Bo Zheng

As advertisers increasingly shift their budgets toward digital advertising, accurately forecasting advertising costs becomes essential for optimizing marketing campaign returns. This paper presents a comprehensive study that employs various…

Machine Learning · Computer Science 2024-08-22 Fynn Oldenburg , Qiwei Han , Maximilian Kaiser

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

Online advertising in E-commerce platforms provides sellers an opportunity to achieve potential audiences with different target goals. Ad serving systems (like display and search advertising systems) that assign ads to pages should satisfy…

Machine Learning · Computer Science 2019-10-09 Chao Wei , Weiru Zhang , Shengjie Sun , Fei Li , Xiaonan Meng , Yi Hu , Hao Wang

In an effort to combat ad annoyance in mobile apps, publishers have introduced a new ad format called "Incentivized Advertising" or "Rewarded Advertising", whereby users receive rewards in exchange for watching ads. There is much debate in…

Applications · Statistics 2021-02-03 Khai Chiong , Sha Yang , Richard Chen

Forecasting click volume is a key task in digital advertising, influencing both revenue and campaign strategy. Traditional time series models rely solely on numerical data, often overlooking rich contextual information embedded in textual…

Information Retrieval · Computer Science 2025-09-15 Briti Gangopadhyay , Zhao Wang , Shingo Takamatsu

Advertisement auctions play a crucial role in revenue generation for e-commerce companies. To make the bidding procedure scalable to thousands of auctions, the automatic bidding (autobidding) algorithms are actively developed in the…

Computer Science and Game Theory · Computer Science 2025-10-23 Andrey Pudovikov , Alexandra Khirianova , Ekaterina Solodneva , Aleksandr Katrutsa , Egor Samosvat , Yuriy Dorn

Many modern commercial sites employ recommender systems to propose relevant content to users. While most systems are focused on maximizing the immediate gain (clicks, purchases or ratings), a better notion of success would be the lifetime…

Machine Learning · Statistics 2017-02-24 Assaf Hallak , Yishay Mansour , Elad Yom-Tov

In contextual dynamic pricing, a seller sequentially prices goods based on contextual information. Buyers will purchase products only if the prices are below their valuations. The goal of the seller is to design a pricing strategy that…

Machine Learning · Statistics 2025-02-14 Matilde Tullii , Solenne Gaucher , Nadav Merlis , Vianney Perchet
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