research-article

Learning to Bid in Revenue Maximizing Auction

Authors:

Thomas Nedelec,

Noureddine El Karoui,

Vianney PerchetAuthors Info & Claims

WWW '19: Companion Proceedings of The 2019 World Wide Web Conference

Pages 934 - 935

https://doi.org/10.1145/3308560.3316527

Published: 13 May 2019 Publication History

Abstract

We consider the problem of the optimization of bidding strategies in prior-dependent revenue-maximizing auctions, when the seller fixes the reserve prices based on the bid distributions. Our study is done in the setting where one bidder is strategic. Using a variational approach, we study the complexity of the original objective and we introduce a relaxation of the objective functional in order to use gradient descent methods. Our approach is simple, general and can be applied to various value distributions and revenue-maximizing mechanisms. The new strategies we derive yield massive uplifts compared to the traditional truthfully bidding strategy.

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Cited By

Hu YHan CGuo TXiao HDastani MSichman JAlechina NDignum V(2024)Applying Opponent Modeling for Automatic Bidding in Online Repeated AuctionsProceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems10.5555/3635637.3662938(843-851)Online publication date: 6-May-2024
https://dl.acm.org/doi/10.5555/3635637.3662938
Chen ZYang MWang CLi JCai ZRen YZhu ZDeng XChua TNgo CKa-Wei Lee RKumar RLauw H(2024)Budget-Constrained Auctions with Unassured Priors: Strategic Equivalence and Structural PropertiesProceedings of the ACM Web Conference 202410.1145/3589334.3645344(14-24)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589334.3645344
Deng XLin TXiao T(2023)Private Data Manipulation in Sponsored Search AuctionsCAAI Artificial Intelligence Research10.26599/AIR.2023.9150024(9150024)Online publication date: Dec-2023
https://doi.org/10.26599/AIR.2023.9150024
Show More Cited By

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Learning to Bid in Revenue Maximizing Auction

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cover image ACM Other conferences

WWW '19: Companion Proceedings of The 2019 World Wide Web Conference

May 2019

1331 pages

ISBN:9781450366755

DOI:10.1145/3308560

Editors:
Ling Liu
Georgia Tech, USA
,
Ryen White
Microsoft Research, USA

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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IW3C2: International World Wide Web Conference Committee

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 May 2019

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WWW '19

WWW '19: The Web Conference

May 13 - 17, 2019

San Francisco, USA

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Hu YHan CGuo TXiao HDastani MSichman JAlechina NDignum V(2024)Applying Opponent Modeling for Automatic Bidding in Online Repeated AuctionsProceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems10.5555/3635637.3662938(843-851)Online publication date: 6-May-2024
https://dl.acm.org/doi/10.5555/3635637.3662938
Chen ZYang MWang CLi JCai ZRen YZhu ZDeng XChua TNgo CKa-Wei Lee RKumar RLauw H(2024)Budget-Constrained Auctions with Unassured Priors: Strategic Equivalence and Structural PropertiesProceedings of the ACM Web Conference 202410.1145/3589334.3645344(14-24)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589334.3645344
Deng XLin TXiao T(2023)Private Data Manipulation in Sponsored Search AuctionsCAAI Artificial Intelligence Research10.26599/AIR.2023.9150024(9150024)Online publication date: Dec-2023
https://doi.org/10.26599/AIR.2023.9150024
Ivanov DSafiulin IFilippov IBalabaeva KKoyejo SMohamed SAgarwal ABelgrave DCho KOh A(2022)Optimal-er auctions through attentionProceedings of the 36th International Conference on Neural Information Processing Systems10.5555/3600270.3602787(34734-34747)Online publication date: 28-Nov-2022
https://dl.acm.org/doi/10.5555/3600270.3602787
Boursier EPerchet V(2022)Utility/privacy trade-off as regularized optimal transportMathematical Programming10.1007/s10107-022-01811-w203:1-2(703-726)Online publication date: 22-Apr-2022
https://doi.org/10.1007/s10107-022-01811-w
Meir RColini-Baldeschi R(2022)Explicitly Simple Near-Tie AuctionsAlgorithmic Game Theory10.1007/978-3-031-15714-1_7(113-130)Online publication date: 14-Sep-2022
https://doi.org/10.1007/978-3-031-15714-1_7
Nedelec TBaudet JPerchet VEl Karoui NDignum FLomuscio AEndriss UNowé A(2021)Adversarial Learning in Revenue-Maximizing AuctionsProceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3463952.3464064(955-963)Online publication date: 3-May-2021
https://dl.acm.org/doi/10.5555/3463952.3464064
Liu APaes Leme RSchneider JLarochelle HRanzato MHadsell RBalcan MLin H(2020)Myersonian regressionProceedings of the 34th International Conference on Neural Information Processing Systems10.5555/3495724.3496490(9135-9144)Online publication date: 6-Dec-2020
https://dl.acm.org/doi/10.5555/3495724.3496490
Tang PWang XWang ZXu YYang XEl Fallah Seghrouchni ASukthankar GAn BYorke-Smith N(2020)Optimized Cost per Mille in Feeds AdvertisingProceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3398761.3398918(1359-1367)Online publication date: 5-May-2020
https://dl.acm.org/doi/10.5555/3398761.3398918
Shen WTang PWang XXu YYang XEl Fallah Seghrouchni ASukthankar GAn BYorke-Smith N(2020)Learning to Design Coupons in Online Advertising MarketsProceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3398761.3398905(1242-1250)Online publication date: 5-May-2020
https://dl.acm.org/doi/10.5555/3398761.3398905
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