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The ad-trading desks of media-buying agencies are increasingly relying on complex algorithms for purchasing advertising inventory. In particular, Real-Time Bidding (RTB) algorithms respond to many auctions -- usually Vickrey auctions --…

Optimization and Control · Mathematics 2016-06-20 Joaquin Fernandez-Tapia , Olivier Guéant , Jean-Michel Lasry

Automated bidding is central to modern digital advertising. Early rule-based methods lacked adaptability, while subsequent Reinforcement Learning approaches modeled bidding as a Markov Decision Process but struggled with long-term…

Artificial Intelligence · Computer Science 2026-05-20 Mingming Zhang , Feiqing Zhuang , Na Li , Shengjie Sun , Xiaowei Chen , Junxiong Zhu , Fei Xiao , Keping Yang , Lixin Zou , Chenliang Li

We study a game between autobidding algorithms that compete in an online advertising platform. Each autobidder is tasked with maximizing its advertiser's total value over multiple rounds of a repeated auction, subject to budget and…

Computer Science and Game Theory · Computer Science 2024-12-03 Brendan Lucier , Sarath Pattathil , Aleksandrs Slivkins , Mengxiao Zhang

Maximizing utility with a budget constraint is the primary goal for advertisers in real-time bidding (RTB) systems. The policy maximizing the utility is referred to as the optimal bidding strategy. Earlier works on optimal bidding strategy…

Machine Learning · Computer Science 2020-04-02 Aritra Ghosh , Saayan Mitra , Somdeb Sarkhel , Viswanathan Swaminathan

In the realm of online advertising, automated bidding has become a pivotal tool, enabling advertisers to efficiently capture impression opportunities in real-time. Recently, generative auto-bidding has shown significant promise, offering…

Information Retrieval · Computer Science 2026-02-27 Yulong Gao , Wan Jiang , Mingzhe Cao , Xuepu Wang , Zeyu Pan , Haonan Yang , Ye Liu , Xin Yang

Auto-bidding, with its strong capability to optimize bidding decisions within dynamic and competitive online environments, has become a pivotal strategy for advertising platforms. Existing approaches typically employ rule-based strategies…

Machine Learning · Computer Science 2025-04-28 Jingtong Gao , Yewen Li , Shuai Mao , Peng Jiang , Nan Jiang , Yejing Wang , Qingpeng Cai , Fei Pan , Peng Jiang , Kun Gai , Bo An , Xiangyu Zhao

We develop a novel optimization model to maximize the profit of a Demand-Side Platform (DSP) while ensuring that the budget utilization preferences of the DSP's advertiser clients are adequately met. Our model is highly flexible and can be…

Optimization and Control · Mathematics 2018-05-31 Alfonso Lobos , Paul Grigas , Zheng Wen , Kuang-chih Lee

Convergence (virtual) bidding is an important part of two-settlement electric power markets as it can effectively reduce discrepancies between the day-ahead and real-time markets. Consequently, there is extensive research into the bidding…

Optimization and Control · Mathematics 2023-02-09 Letif Mones , Sean Lovett

Online auction scenarios, such as bidding searches on advertising platforms, often require bidders to participate repeatedly in auctions for identical or similar items. Most previous studies have only considered the process by which the…

Computer Science and Game Theory · Computer Science 2024-02-28 Yudong Hu , Congying Han , Tiande Guo , Hao Xiao

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

As data marketplaces become increasingly central to the digital economy, it is crucial to design efficient pricing mechanisms that optimize revenue while ensuring fair and adaptive pricing. We introduce the Maximum Auction-to-Posted Price…

Machine Learning · Statistics 2026-04-06 Yingqi Gao , Wenlu Xu , Jin J. Zhou , Hua Zhou , Yong Chen , Xiaowu Dai

Real-Time Bidding (RTB) display advertising is a method for purchasing display advertising inventory in auctions that occur within milliseconds. The performance of RTB campaigns is generally measured with a series of Key Performance…

Computer Science and Game Theory · Computer Science 2020-07-02 Michael Tashman , Jiayi Xie , John Hoffman , Lee Winikor , Rouzbeh Gerami

The majority of online display ads are served through real-time bidding (RTB) --- each ad display impression is auctioned off in real-time when it is just being generated from a user visit. To place an ad automatically and optimally, it is…

Machine Learning · Computer Science 2017-01-13 Han Cai , Kan Ren , Weinan Zhang , Kleanthis Malialis , Jun Wang , Yong Yu , Defeng Guo

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

Automated bidding to optimize online advertising with various constraints, e.g. ROI constraints and budget constraints, is widely adopted by advertisers. A key challenge lies in designing algorithms for non-truthful mechanisms with ROI…

Computer Science and Game Theory · Computer Science 2025-10-21 Yuan Deng , Yilin Li , Wei Tang , Hanrui Zhang

Generative Retrieval (GR) is rapidly transforming e-commerce search by replacing traditional multi-stage pipelines with the autoregressive decoding of structured Semantic IDs (SIDs). Despite this architectural efficiency, aligning GR models…

Information Retrieval · Computer Science 2026-04-29 Zhiguo Chen , Guohao Sun , Yiming Qiu , Xingzhi Yao , Mingming Li , Huimu Wang , Yangqi Zhang , Songlin Wang , Sulong Xu

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

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

Budget management strategies in repeated auctions have received growing attention in online advertising markets. However, previous work on budget management in online bidding mainly focused on second-price auctions. The rapid shift from…

Computer Science and Game Theory · Computer Science 2023-04-27 Qian Wang , Zongjun Yang , Xiaotie Deng , Yuqing Kong

Real-time bidding (RTB) is an important mechanism in online display advertising, where a proper bid for each page view plays an essential role for good marketing results. Budget constrained bidding is a typical scenario in RTB where the…

Artificial Intelligence · Computer Science 2018-10-24 Di Wu , Xiujun Chen , Xun Yang , Hao Wang , Qing Tan , Xiaoxun Zhang , Jian Xu , Kun Gai