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- research-articleAugust 2024
Generative Auto-bidding via Conditional Diffusion Modeling
KDD '24: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data MiningPages 5038–5049https://doi.org/10.1145/3637528.3671526Auto-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 modeled through ...
- research-articleAugust 2023
A Personalized Automated Bidding Framework for Fairness-aware Online Advertising
- Haoqi Zhang,
- Lvyin Niu,
- Zhenzhe Zheng,
- Zhilin Zhang,
- Shan Gu,
- Fan Wu,
- Chuan Yu,
- Jian Xu,
- Guihai Chen,
- Bo Zheng
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningPages 5544–5553https://doi.org/10.1145/3580305.3599765Powered by machine learning techniques, online advertising platforms have launched various automated bidding strategy services to facilitate intelligent decision-making for advertisers. However, advertisers experience heterogeneous advertising ...
- research-articleFebruary 2023
Boosting Advertising Space: Designing Ad Auctions for Augment Advertising
WSDM '23: Proceedings of the Sixteenth ACM International Conference on Web Search and Data MiningPages 1066–1074https://doi.org/10.1145/3539597.3570381In online e-commerce platforms, sponsored ads are always mixed with non-sponsored organic content (recommended items). To guarantee user experience, online platforms always impose strict limitations on the number of ads displayed, becoming the bottleneck ...
- research-articleFebruary 2022
A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online Advertising
- 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
WSDM '22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data MiningPages 1129–1139https://doi.org/10.1145/3488560.3498373In 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 tools from the ...
- research-articleAugust 2021
Neural Auction: End-to-End Learning of Auction Mechanisms for E-Commerce Advertising
- Xiangyu Liu,
- Chuan Yu,
- Zhilin Zhang,
- Zhenzhe Zheng,
- Yu Rong,
- Hongtao Lv,
- Da Huo,
- Yiqing Wang,
- Dagui Chen,
- Jian Xu,
- Fan Wu,
- Guihai Chen,
- Xiaoqiang Zhu
KDD '21: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data MiningPages 3354–3364https://doi.org/10.1145/3447548.3467103In e-commerce advertising, it is crucial to jointly consider various performance metrics, e.g., user experience, advertiser utility, and platform revenue. Traditional auction mechanisms, such as GSP and VCG auctions, can be suboptimal due to their fixed ...
- research-articleMarch 2021
Optimizing Multiple Performance Metrics with Deep GSP Auctions for E-commerce Advertising
- Zhilin Zhang,
- Xiangyu Liu,
- Zhenzhe Zheng,
- Chenrui Zhang,
- Miao Xu,
- Junwei Pan,
- Chuan Yu,
- Fan Wu,
- Jian Xu,
- Kun Gai
WSDM '21: Proceedings of the 14th ACM International Conference on Web Search and Data MiningPages 993–1001https://doi.org/10.1145/3437963.3441771In e-commerce advertising, the ad platform usually relies on auction mechanisms to optimize different performance metrics, such as user experience, advertiser utility, and platform revenue. However, most of the state-of-the-art auction mechanisms only ...