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Existing advertisements click-through rate (CTR) prediction models are mainly dependent on behavior ID features, which are learned based on the historical user-ad interactions. Nevertheless, behavior ID features relying on historical user…

Information Retrieval · Computer Science 2022-09-26 Tan Yu , Zhipeng Jin , Jie Liu , Yi Yang , Hongliang Fei , Ping Li

Auto-bidding is crucial in facilitating online advertising by automatically providing bids for advertisers. While previous work has made great efforts to model bidding environments for better ad performance, it has limitations in…

Artificial Intelligence · Computer Science 2026-03-17 Jiahao Ji , Tianyu Wang , Yeshu Li , Yushen Huo , Zhilin Zhang , Chuan Yu , Jian Xu , Bo Zheng

In computational advertising, a challenging problem is how to recommend the bid for advertisers to achieve the best return on investment (ROI) given budget constraint. This paper presents a bid recommendation scenario that discovers the…

Information Retrieval · Computer Science 2022-12-29 Deguang Kong , Konstantin Shmakov , Jian Yang

Auto-bidding is a crucial task in real-time advertising markets, where policies must optimize long-horizon value under delivery constraints (e.g., budget and CPA). Existing methods for auto-bidding rely on compact numerical state…

Artificial Intelligence · Computer Science 2026-05-08 Guanyu Zhu , Jining Luan , Hanwen Du , Xinyu Fang , Sibo Xu , Ersheng Ni , Hongji Li , Jincheng Fang , Ronghao Chen , Huacan Wang , Xuanqi Lan , Yongxin Ni , Yiqi Sun , Youhua Li

In online advertising markets, budget-constrained advertisers acquire ad placements through repeated bidding in auctions on various platforms. We present a strategy for bidding optimally in a set of auctions that may or may not be…

Computer Science and Game Theory · Computer Science 2023-06-14 Fransisca Susan , Negin Golrezaei , Okke Schrijvers

There are two major ways of selling impressions in display advertising. They are either sold in spot through auction mechanisms or in advance via guaranteed contracts. The former has achieved a significant automation via real-time bidding…

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

For Verizon MediaDemand Side Platform(DSP), forecasting of ad campaign performance not only feeds key information to the optimization server to allow the system to operate on a high-performance mode, but also produces actionable insights to…

Machine Learning · Statistics 2021-07-16 Hao He , Tian Zhou , Lihua Ren , Niklas Karlsson , Aaron Flores

Multiple content providers rely on native advertisement for revenue by placing ads within the organic content of their pages. We refer to this setting as ``queryless'' to differentiate from search advertisement where a user submits a search…

Information Retrieval · Computer Science 2021-01-01 Iyad Batal , Akshay Soni

Click-Through Rate (CTR) prediction, crucial in applications like recommender systems and online advertising, involves ranking items based on the likelihood of user clicks. User behavior sequence modeling has marked progress in CTR…

Information Retrieval · Computer Science 2023-08-22 Hengyu Zhang , Chang Meng , Wei Guo , Huifeng Guo , Jieming Zhu , Guangpeng Zhao , Ruiming Tang , Xiu Li

In online display advertising, guaranteed contracts and real-time bidding (RTB) are two major ways to sell impressions for a publisher. For large publishers, simultaneously selling impressions through both guaranteed contracts and in-house…

Computer Science and Game Theory · Computer Science 2022-03-15 Di Wu , Cheng Chen , Xiujun Chen , Junwei Pan , Xun Yang , Qing Tan , Jian Xu , Kuang-Chih Lee

Real-time bidding (RTB) has become one of the largest online advertising markets in the world. Today the bid price per ad impression is typically decided by the expected value of how it can lead to a desired action event (e.g., registering…

Computer Science and Game Theory · Computer Science 2016-02-16 Jian Xu , Xuhui Shao , Jianjie Ma , Kuang-chih Lee , Hang Qi , Quan Lu

Causally identifying the effect of digital advertising is challenging, because experimentation is expensive, and observational data lacks random variation. This paper identifies a pervasive source of naturally occurring, quasi-experimental…

Econometrics · Economics 2022-02-18 George Gui , Harikesh Nair , Fengshi Niu

Treatment allocation under budget constraints is a central challenge in digital advertising: advertisers must decide which users to show ads to while spending a limited budget wisely. The standard approach follows a two-stage offline…

Machine Learning · Computer Science 2026-04-30 Abhirami Pillai

Advertising click-through rate (CTR) prediction aims to forecast the probability that a user will click on an advertisement in a given context, thus providing enterprises with decision support for product ranking and ad placement. However,…

Machine Learning · Computer Science 2024-11-26 Xiaowei Xi , Song Leng , Yuqing Gong , Dalin Li

We develop a framework for the analysis of large-scale Ad-auctions where adverts are assigned over a continuum of search types. For this pay-per-click market, we provide an efficient mechanism that maximizes social welfare. In particular,…

Computer Science and Game Theory · Computer Science 2016-06-03 Frank Kelly , Peter Key , Neil Walton

Sponsored search represents a major source of revenue for web search engines. This popular advertising model brings a unique possibility for advertisers to target users' immediate intent communicated through a search query, usually by…

In online advertising, the inherent complexity and dynamic nature of advertising environments necessitate the use of auto-bidding services to assist advertisers in bid optimization. This complexity is further compounded in multi-channel…

Artificial Intelligence · Computer Science 2026-02-27 Xinxin Yang , Yangyang Tang , Yikun Zhou , Yaolei Liu , Yun Li , Bo Yang

Display advertising provides significant value to advertisers, publishers, and users. Traditional display advertising systems utilize a multi-stage architecture consisting of retrieval, coarse ranking, and final ranking. However,…

Information Retrieval · Computer Science 2025-07-17 Fengxin Li , Yi Li , Yue Liu , Chao Zhou , Yuan Wang , Xiaoxiang Deng , Wei Xue , Dapeng Liu , Lei Xiao , Haijie Gu , Jie Jiang , Hongyan Liu , Biao Qin , Jun He

In real-world search, recommendation, and advertising systems, the multi-stage ranking architecture is commonly adopted. Such architecture usually consists of matching, pre-ranking, ranking, and re-ranking stages. In the pre-ranking stage,…

Information Retrieval · Computer Science 2021-05-18 Xu Ma , Pengjie Wang , Hui Zhao , Shaoguo Liu , Chuhan Zhao , Wei Lin , Kuang-Chih Lee , Jian Xu , Bo Zheng

Online advertisement is the main source of revenue for Internet business. Advertisers are typically ranked according to a score that takes into account their bids and potential click-through rates(eCTR). Generally, the likelihood that a…

Machine Learning · Statistics 2018-07-06 Lulu Wang , Huahui Liu , Guanhao Chen , Shaola Ren , Xiaonan Meng , Yi Hu
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