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Traditional auction theory posits that bid value exhibits a positive correlation with the probability of securing the auctioned object in ascending auctions. However, under uncertainty and incomplete information, as is characteristic in…

Theoretical Economics · Economics 2025-12-19 Dipankar Das

Auto-bidding is essential in facilitating online advertising by automatically placing bids on behalf of advertisers. Generative auto-bidding, which generates bids based on an adjustable condition using models like transformers and…

Artificial Intelligence · Computer Science 2025-06-04 Yewen Li , Shuai Mao , Jingtong Gao , Nan Jiang , Yunjian Xu , Qingpeng Cai , Fei Pan , Peng Jiang , Bo An

Auto-bidding is widely used in advertising systems, serving a diverse range of advertisers. Generative bidding is increasingly gaining traction due to its strong planning capabilities and generalizability. Unlike traditional reinforcement…

Machine Learning · Computer Science 2025-08-26 Yunshan Peng , Wenzheng Shu , Jiahao Sun , Yanxiang Zeng , Jinan Pang , Wentao Bai , Yunke Bai , Xialong Liu , Peng Jiang

This paper describes a new win-rate based bid shading algorithm (WR) that does not rely on the minimum-bid-to-win feedback from a Sell-Side Platform (SSP). The method uses a modified logistic regression to predict the profit from each…

Computer Science and Game Theory · Computer Science 2020-09-22 Shengjun Pan , Brendan Kitts , Tian Zhou , Hao He , Bharatbhushan Shetty , Aaron Flores , Djordje Gligorijevic , Junwei Pan , Tingyu Mao , San Gultekin , Jianlong Zhang

Online auctions play a central role in online advertising, and are one of the main reasons for the industry's scalability and growth. With great changes in how auctions are being organized, such as changing the second- to first-price…

Computer Science and Game Theory · Computer Science 2020-09-04 Djordje Gligorijevic , Tian Zhou , Bharatbhushan Shetty , Brendan Kitts , Shengjun Pan , Junwei Pan , Aaron Flores

Auto-bidding plays a crucial role in facilitating online advertising by automatically providing bids for advertisers. Reinforcement learning (RL) has gained popularity for auto-bidding. However, most current RL auto-bidding methods are…

Machine Learning · Computer Science 2024-10-10 Jiayan Guo , Yusen Huo , Zhilin Zhang , Tianyu Wang , Chuan Yu , Jian Xu , Yan Zhang , Bo Zheng

Modern auto-bidding systems are required to balance overall performance with diverse advertiser goals and real-world constraints, reflecting the dynamic and evolving needs of the industry. Recent advances in conditional generative models,…

Machine Learning · Computer Science 2025-12-09 Yu Lei , Jiayang Zhao , Yilei Zhao , Zhaoqi Zhang , Linyou Cai , Qianlong Xie , Xingxing Wang

Online bidding and auction are crucial aspects of the online advertising industry. Conventionally, there is only one slot for ad display and most current studies focus on it. Nowadays, multi-slot display advertising is gradually becoming…

Computer Science and Game Theory · Computer Science 2024-03-06 Zhen Gong , Lvyin Niu , Yang Zhao , Miao Xu , Zhenzhe Zheng , Haoqi Zhang , Zhilin Zhang , Fan Wu , Rongquan Bai , Chuan Yu , Jian Xu , Bo Zheng

Auto-bidding services optimize real-time bidding strategies for advertisers under key performance indicator (KPI) constraints such as target return on investment and budget. However, uncertainties such as model prediction errors and…

Computer Science and Game Theory · Computer Science 2026-04-08 Linghui Meng , Chun Gan , Shengsheng Niu , Chengcheng Zhang , Chenchen Li , Chuan Yang , Yi Mao , Xin Zhu , Jie He , Zhangang Lin , Ching Law

The most significant progress in recent years in online display advertising is what is known as the Real-Time Bidding (RTB) mechanism to buy and sell ads. RTB essentially facilitates buying an individual ad impression in real time while it…

Computer Science and Game Theory · Computer Science 2017-07-18 Jun Wang , Weinan Zhang , Shuai Yuan

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

In programmatic advertising, ad slots are usually sold using second-price (SP) auctions in real-time. The highest bidding advertiser wins but pays only the second-highest bid (known as the winning price). In SP, for a single item, the…

Machine Learning · Computer Science 2020-01-22 Aritra Ghosh , Saayan Mitra , Somdeb Sarkhel , Jason Xie , Gang Wu , Viswanathan Swaminathan

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

Bid shading has become a standard practice in the digital advertising industry, in which most auctions for advertising (ad) opportunities are now of first price type. Given an ad opportunity, performing bid shading requires estimating not…

Computer Science and Game Theory · Computer Science 2024-10-22 Yanlin Qu , Ravi Kant , Yan Chen , Brendan Kitts , San Gultekin , Aaron Flores , Jose Blanchet

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

Real-time bidding (RTB) based display advertising has become one of the key technological advances in computational advertising. RTB enables advertisers to buy individual ad impressions via an auction in real-time and facilitates the…

Computer Science and Game Theory · Computer Science 2018-03-13 Kan Ren , Weinan Zhang , Ke Chang , Yifei Rong , Yong Yu , Jun Wang

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

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

Auto-bidding is central to computational advertising, achieving notable commercial success by optimizing advertisers' bids within economic constraints. Recently, large generative models show potential to revolutionize auto-bidding by…

Computer Science and Game Theory · Computer Science 2025-09-04 Yewen Li , Jingtong Gao , Nan Jiang , Shuai Mao , Ruyi An , Fei Pan , Xiangyu Zhao , Bo An , Qingpeng Cai , Peng Jiang

Auto-bidding systems aim to maximize advertiser value over long horizons under budget constraints and ratio targets such as cost-per-acquisition, yet future traffic and auction dynamics are non-stationary and uncertain. Existing approaches…

Artificial Intelligence · Computer Science 2026-05-28 Eunseok Yang , Xingdong Zuo , Kyung-Min Kim
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