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Where to Sell: Simulating Auctions From Learning Algorithms

Published: 21 July 2016 Publication History

Abstract

Ad exchange platforms connect online publishers and advertisers and facilitate the sale of billions of impressions every day. We study these environments from the perspective of a publisher who wants to find the profit-maximizing exchange in which to sell his inventory. Ideally, the publisher would run an auction among exchanges. However, this is not usually possible due to practical business considerations. Instead, the publisher must send each impression to only one of the exchanges, along with an asking price. We model the problem as a variation of the multi-armed bandits problem in which exchanges (arms) can behave strategically in order to maximizes their own profit. We propose e mechanisms that find the best exchange with sub-linear regret and have desirable incentive properties.

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  • (2024)Dynamic Mechanism Design via AI-Driven ApproachesAI-Driven Mechanism Design10.1007/978-981-97-9286-3_3(53-93)Online publication date: 30-Sep-2024
  • (2021)Incentive-Compatible Learning of Reserve Prices for Repeated AuctionsOperations Research10.1287/opre.2020.200769:2(509-524)Online publication date: Mar-2021
  • (2021)Boosted Second Price AuctionsProceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining10.1145/3447548.3467454(447-457)Online publication date: 14-Aug-2021
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cover image ACM Conferences
EC '16: Proceedings of the 2016 ACM Conference on Economics and Computation
July 2016
874 pages
ISBN:9781450339360
DOI:10.1145/2940716
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 21 July 2016

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  1. strategic bandits

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EC '16
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EC '16: ACM Conference on Economics and Computation
July 24 - 28, 2016
Maastricht, The Netherlands

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EC '16 Paper Acceptance Rate 80 of 242 submissions, 33%;
Overall Acceptance Rate 664 of 2,389 submissions, 28%

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Cited By

View all
  • (2024)Dynamic Mechanism Design via AI-Driven ApproachesAI-Driven Mechanism Design10.1007/978-981-97-9286-3_3(53-93)Online publication date: 30-Sep-2024
  • (2021)Incentive-Compatible Learning of Reserve Prices for Repeated AuctionsOperations Research10.1287/opre.2020.200769:2(509-524)Online publication date: Mar-2021
  • (2021)Boosted Second Price AuctionsProceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining10.1145/3447548.3467454(447-457)Online publication date: 14-Aug-2021
  • (undefined)How Do Tumor Cytogenetics Inform Cancer Treatments? Dynamic Risk Stratification and Precision Medicine Using Multi-armed BanditsSSRN Electronic Journal10.2139/ssrn.3405082
  • (undefined)Dynamic Reserves for Repeated Second Price AuctionsSSRN Electronic Journal10.2139/ssrn.2444495

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