Competition
Auto-Bidding in Large-Scale Auctions: Learning Decision-Making in Uncertain and Competitive Games
Jian Xu · ZHILIN ZHANG · Zongqing Lu · Xiaotie Deng · Michael Wellman · Chuan Yu · Shuai Dou · Yusen Huo · Zhiwei Xu · Zhijian Duan · Shaopan Xiong · Chuang Liu · Ningyuan Li · Kefan Su · Wei Gong · Bo Zheng
West Meeting Room 210
Decision-making in large-scale games is an essential research area in artificial intelligence with significant real-world impact. An agent confronts the critical task of making high-frequency strategic decisions in an uncertain and competitive environment, characterized by significant randomness and rapidly changing strategies from massive competitors. However, the shortage of large-scale, realistic game systems and datasets has hindered research progress in this area. To provide opportunities for in-depth research on this highly valuable problem, we present the Auto-Bidding in Large-Scale Auctions challenge derived from online advertising, a booming \$626.8 billion industry in 2023. We have developed a standardized ad auction system for the competition, which reproduces the characteristics of real-world large-scale games and incorporates essential features that deserve research attention. We also provide a training framework with a 500-million-record dataset and several industry-proven methods as baselines to help participants quickly start and deeply optimize their strategies.Furthermore, we have prepared a comprehensive promotional strategy, raised sufficient funds, and offered varied incentives to attract more participants from diverse backgrounds.We believe that the proposed competition will provide opportunities for more researchers to gain insights and conduct research in this field, driving technical innovation for both research and real-world practical applications.
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Schedule
Sat 1:30 p.m. - 1:40 p.m.
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Opening remarks
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Opening
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Bo Zheng 🔗 |
Sat 1:40 p.m. - 1:50 p.m.
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Alimama's Large-Scale Advertising System and Dataset Announcement
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intro
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Jian Xu 🔗 |
Sat 1:50 p.m. - 2:20 p.m.
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Adaptive Control for Auto-bidding in Programmatic Advertising
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Invited talk
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Niklas Karlsson 🔗 |
Sat 2:20 p.m. - 2:35 p.m.
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AIGB Track Winner (KGAB) Presentation
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Presentation
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SlidesLive Video |
Jingtong Gao · Shuai Mao · Yewen Li · Nan Jiang · Qingpeng Cai 🔗 |
Sat 2:35 p.m. - 2:50 p.m.
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AIGB Track Winner (CleanDiffuser) Presentation
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Presentation
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SlidesLive Video |
Zhenrui Zheng · Yifu Yuan · Zibin Dong · Yi Ma 🔗 |
Sat 2:50 p.m. - 3:20 p.m.
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Combinatorial Bandits with Full Bandit Feedback
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Invited talk
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Vaneet Aggarwal 🔗 |
Sat 3:20 p.m. - 3:30 p.m.
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Break
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🔗 |
Sat 3:30 p.m. - 3:45 p.m.
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General Track Winner (Dsat2) Presentation
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Presentation
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SlidesLive Video |
Alberto Silvio Chiappa · Briti Gangopadhyay 🔗 |
Sat 3:45 p.m. - 4:15 p.m.
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Auto-bidding in Online Advertising: Bidding Algorithms and Auction Design
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Invited talk
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Mingfei Zhao 🔗 |
Sat 4:15 p.m. - 4:30 p.m.
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General Track Winner (名个这就) Presentation
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Presentation
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Qingmao Yao · Haoran Sun · Tingting Meng · Hao Xu · Chu Xu 🔗 |