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This paper explores the integration of strategic optimization methods in search advertising, focusing on ad ranking and bidding mechanisms within E-commerce platforms. By employing a combination of reinforcement learning and evolutionary…

Machine Learning · Computer Science 2024-05-30 Chang Zhou , Yang Zhao , Jin Cao , Yi Shen , Xiaoling Cui , Chiyu Cheng

The optimization of bidding strategies for online advertising slot auctions presents a critical challenge across numerous digital marketplaces. A significant obstacle to the development, evaluation, and refinement of real-time autobidding…

Online Real-Time Bidding (RTB) is a complex auction game among which advertisers struggle to bid for ad impressions when a user request occurs. Considering display cost, Return on Investment (ROI), and other influential Key Performance…

Artificial Intelligence · Computer Science 2022-07-07 Haolin Zhou , Chaoqi Yang , Xiaofeng Gao , Qiong Chen , Gongshen Liu , Guihai Chen

Internet advertisers (buyers) repeatedly procure ad impressions from ad platforms (sellers) with the aim to maximize total conversion (i.e. ad value) while respecting both budget and return-on-investment (ROI) constraints for efficient…

Computer Science and Game Theory · Computer Science 2023-02-08 Negin Golrezaei , Patrick Jaillet , Jason Cheuk Nam Liang , Vahab Mirrokni

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

This research focuses on the bid optimization problem in the real-time bidding setting for online display advertisements, where an advertiser, or the advertiser's agent, has access to the features of the website visitor and the type of ad…

Machine Learning · Computer Science 2022-10-31 Rui Fan , Erick Delage

We study and formulate arbitrage in display advertising. Real-Time Bidding (RTB) mimics stock spot exchanges and utilises computers to algorithmically buy display ads per impression via a real-time auction. Despite the new automation, the…

Computer Science and Game Theory · Computer Science 2015-06-15 Weinan Zhang , Jun Wang

In display advertising, a small group of sellers and bidders face each other in up to 10 12 auctions a day. In this context, revenue maximisation via monopoly price learning is a high-value problem for sellers. By nature, these auctions are…

Machine Learning · Computer Science 2020-10-21 Lorenzo Croissant , Marc Abeille , Clément Calauzènes

In this paper, we analyze a natural learning algorithm for uniform pacing of advertising budgets, equipped to adapt to varying ad sale platform conditions. On the demand side, advertisers face a fundamental technical challenge in automating…

Computer Science and Game Theory · Computer Science 2022-11-14 MohammadTaghi Hajiaghayi , Max Springer

We study the problem of finding the optimal bidding strategy for an advertiser in a multi-platform auction setting. The competition on a platform is captured by a value and a cost function, mapping bidding strategies to value and cost…

Computer Science and Game Theory · Computer Science 2025-02-27 Gagan Aggarwal , Anupam Gupta , Xizhi Tan , Mingfei Zhao

Real-time bidding (RTB) plays a pivotal role in online advertising ecosystems. Advertisers employ strategic bidding to optimize their advertising impact while adhering to various financial constraints, such as the return-on-investment (ROI)…

Artificial Intelligence · Computer Science 2024-12-30 Shenghong He , Chao Yu

Online display advertising is growing rapidly in recent years thanks to the automation of the ad buying process. Real-time bidding (RTB) allows the automated trading of ad impressions between advertisers and publishers through real-time…

Machine Learning · Computer Science 2020-08-31 Yang Qiu , Nikolaos Tziortziotis , Martial Hue , Michalis Vazirgiannis

Incrementality, which is used to measure the causal effect of showing an ad to a potential customer (e.g. a user in an internet platform) versus not, is a central object for advertisers in online advertising platforms. This paper…

Machine Learning · Computer Science 2023-01-18 Ashwinkumar Badanidiyuru , Zhe Feng , Tianxi Li , Haifeng Xu

Internet live streaming is widely used in online entertainment and e-commerce, where live advertising is an important marketing tool for anchors. An advertising campaign hopes to maximize the effect (such as conversions) under constraints…

Machine Learning · Statistics 2025-08-11 Bo Yang , Ruixuan Luo , Junqi Jin , Han Zhu

With the emergence of new online channels and information technology, digital advertising tends to substitute more and more to traditional advertising by offering the opportunity to companies to target the consumers/users that are really…

Optimization and Control · Mathematics 2021-11-17 Médéric Motte , Huyên Pham

Group-buying ads seeking a minimum number of customers before the deal expiry are increasingly used by the daily-deal providers. Unlike the traditional web ads, the advertiser's profits for group-buying ads depends on the time to expiry and…

Computer Science and Game Theory · Computer Science 2012-06-05 Raju Balakrishnan , Rushi P Bhatt

We consider the problem of bidding in online advertising, where an advertiser aims to maximize value while adhering to budget and Return-on-Spend (RoS) constraints. Unlike prior work that assumes knowledge of the value generated by winning…

Machine Learning · Computer Science 2025-03-06 Sushant Vijayan , Zhe Feng , Swati Padmanabhan , Karthikeyan Shanmugam , Arun Suggala , Di Wang

Managing millions of digital auctions is an essential task for modern advertising auction systems. The main approach to managing digital auctions is an autobidding approach, which depends on the Click-Through Rate and Conversion Rate…

Computer Science and Game Theory · Computer Science 2025-10-13 Andrey Pudovikov , Alexandra Khirianova , Ekaterina Solodneva , Gleb Molodtsov , Aleksandr Katrutsa , Yuriy Dorn , Egor Samosvat

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

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