Optimizing Multiple Performance Metrics with Deep GSP Auctions for E-commerce Advertising

Author:

Zhang Zhilin1,Liu Xiangyu1,Zheng Zhenzhe2,Zhang Chenrui3,Xu Miao1,Pan Junwei4,Yu Chuan1,Wu Fan2,Xu Jian1,Gai Kun1

Affiliation:

1. Alibaba Group, Beijing, China

2. Shanghai Jiao Tong University, Shanghai, China

3. Peking University, Beijing, China

4. Yahoo Research, Sunnyvale, CA, USA

Funder

Alibaba Innovation Research Program

China NSF grant

Science and Technology Innovation 2030 ? New Generation Artificial Intelligence Major Project

Shanghai Science and Technology fund

Publisher

ACM

Reference27 articles.

1. 2020. Supplementary Materials. https://drive.google.com/file/d/1nTBTaKK5n9NUvf1k7iXNzVhY5vjb3U7J/view?usp=sharing 2020. Supplementary Materials. https://drive.google.com/file/d/1nTBTaKK5n9NUvf1k7iXNzVhY5vjb3U7J/view?usp=sharing

2. Optimising trade-offs among stakeholders in ad auctions

3. Optimizing Trade-offs Among Stakeholders in Real-Time Bidding by Incorporating Multimedia Metrics

4. Self-interested automated mechanism design and implications for optimal combinatorial auctions

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1. EdgeNet : Encoder-decoder generative Network for Auction Design in E-commerce Online Advertising;Proceedings of the 32nd ACM International Conference on Information and Knowledge Management;2023-10-21

2. Learning-Based Ad Auction Design with Externalities: The Framework and A Matching-Based Approach;Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2023-08-04

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4. Breaking the traditional: a survey of algorithmic mechanism design applied to economic and complex environments;Neural Computing and Applications;2023-05-20

5. Ad Auction Design with Coupon-Dependent Conversion Rate in the Auto-bidding World;Proceedings of the ACM Web Conference 2023;2023-04-30

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