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Displaying banner advertisements (in short, ads) on webpages has usually been discussed as an Internet economics topic where a publisher uses auction models to sell an online user's page view to advertisers and the one with the highest bid…

Computer Science and Game Theory · Computer Science 2017-08-02 Xiang Chen , Bowei Chen , Mohan Kankanhalli

Real-time bidding is the new paradigm of programmatic advertising. An advertiser wants to make the intelligent choice of utilizing a \textbf{Demand-Side Platform} to improve the performance of their ad campaigns. Existing approaches are…

Artificial Intelligence · Computer Science 2022-09-14 Yining Lu , Changjie Lu , Naina Bandyopadhyay , Manoj Kumar , Gaurav Gupta

Real-Time Bidding (RTB) is an important paradigm in display advertising, where advertisers utilize extended information and algorithms served by Demand Side Platforms (DSPs) to improve advertising performance. A common problem for DSPs is…

Computer Science and Game Theory · Computer Science 2019-05-30 Xun Yang , Yasong Li , Hao Wang , Di Wu , Qing Tan , Jian Xu , Kun Gai

In this paper, we consider the problem of optimizing the revenue a web publisher gets through real-time bidding (i.e. from ads sold in real-time auctions) and direct (i.e. from ads sold through contracts agreed in advance). We consider a…

Computer Science and Game Theory · Computer Science 2020-06-15 Grégoire Jauvion , Nicolas Grislain

Real-time bidding has emerged as an effective online advertising technique. With real-time bidding, advertisers can position ads per impression, enabling them to optimise ad campaigns by targeting specific audiences in real-time. This paper…

Information Retrieval · Computer Science 2023-05-09 Parikshit Sharma

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

We study the problem of allocating impressions to sellers in e-commerce websites, such as Amazon, eBay or Taobao, aiming to maximize the total revenue generated by the platform. We employ a general framework of reinforcement mechanism…

Multiagent Systems · Computer Science 2018-02-28 Qingpeng Cai , Aris Filos-Ratsikas , Pingzhong Tang , Yiwei Zhang

Multi-agent Reinforcement Learning (MARL) is a powerful tool for training autonomous agents acting independently in a common environment. However, it can lead to sub-optimal behavior when individual incentives and group incentives diverge.…

Artificial Intelligence · Computer Science 2024-01-30 Andreas A. Haupt , Phillip J. K. Christoffersen , Mehul Damani , Dylan Hadfield-Menell

Display advertising is an important online advertising type where banner advertisements (shortly ad) on websites are usually measured by how many times they are viewed by online users. There are two major channels to sell ad views. They can…

Computer Science and Game Theory · Computer Science 2017-01-20 Bowei Chen

Ad exchanges are becoming an increasingly popular way to sell advertisement slots on the internet. An ad exchange is basically a spot market for ad impressions. A publisher who has already signed contracts reserving advertisement…

Data Structures and Algorithms · Computer Science 2016-04-20 Wolfgang Dvořák , Monika Henzinger

Real-Time Bidding (RTB) is an important mechanism in modern online advertising systems. Advertisers employ bidding strategies in RTB to optimize their advertising effects subject to various financial requirements, especially the…

Machine Learning · Computer Science 2022-07-19 Haozhe Wang , Chao Du , Panyan Fang , Shuo Yuan , Xuming He , Liang Wang , Bo Zheng

Real-Time Bidding (RTB) enables advertisers to place competitive bids on impression opportunities instantaneously, striving for cost-effectiveness in a highly competitive landscape. Although RTB has widely benefited from the utilization of…

Artificial Intelligence · Computer Science 2025-02-04 Leng Cai , Junxuan He , Yikai Li , Junjie Liang , Yuanping Lin , Ziming Quan , Yawen Zeng , Jin Xu

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

Iterative combinatorial auctions are widely used in high stakes settings such as spectrum auctions. Such auctions can be hard to analyze, making it difficult for bidders to determine how to behave and for designers to optimize auction rules…

Computer Science and Game Theory · Computer Science 2024-07-25 Greg d'Eon , Neil Newman , Kevin Leyton-Brown

Real-Time Bidding (RTB) is revolutionising display advertising by facilitating per-impression auctions to buy ad impressions as they are being generated. Being able to use impression-level data, such as user cookies, encourages user…

Computer Science and Game Theory · Computer Science 2016-03-04 Weinan Zhang , Yifei Rong , Jun Wang , Tianchi Zhu , Xiaofan Wang

Bidding strategies that help advertisers determine bidding prices are receiving increasing attention as more and more ad impressions are sold through real-time bidding systems. This paper first describes the problem and challenges of…

Computer Science and Game Theory · Computer Science 2022-12-06 Mengjuan Liu , Zhengning Hu , Zhi Lai , Daiwei Zheng , Xuyun Nie

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

Online advertising in recommendation platforms has gained significant attention, with a predominant focus on channel recommendation and budget allocation strategies. However, current offline reinforcement learning (RL) methods face…

Information Retrieval · Computer Science 2025-07-10 Langming Liu , Wanyu Wang , Chi Zhang , Bo Li , Hongzhi Yin , Xuetao Wei , Wenbo Su , Bo Zheng , Xiangyu Zhao

Real time bidding (RTB) enables demand side platforms (bidders) to scale ad campaigns across multiple publishers affiliated to an RTB ad exchange. While driving multiple campaigns for mobile app install ads via RTB, the bidder typically has…

Computer Science and Game Theory · Computer Science 2018-11-13 Anit Kumar Sahu , Shaunak Mishra , Narayan Bhamidipati

In online advertising, auto-bidding has become an essential tool for advertisers to optimize their preferred ad performance metrics by simply expressing high-level campaign objectives and constraints. Previous works designed auto-bidding…

Multiagent Systems · Computer Science 2022-01-06 Chao Wen , Miao Xu , Zhilin Zhang , Zhenzhe Zheng , Yuhui Wang , Xiangyu Liu , Yu Rong , Dong Xie , Xiaoyang Tan , Chuan Yu , Jian Xu , Fan Wu , Guihai Chen , Xiaoqiang Zhu , Bo Zheng