License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.FORC.2022.4
URN: urn:nbn:de:0030-drops-165272
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2022/16527/
Chawla, Shuchi ;
Rezvan, Rojin ;
Sauerberg, Nathaniel
Individually-Fair Auctions for Multi-Slot Sponsored Search
Abstract
We design fair sponsored search auctions that achieve a near-optimal tradeoff between fairness and quality. Our work builds upon the model and auction design of Chawla and Jagadeesan [Chawla and Jagadeesan, 2022], who considered the special case of a single slot. We consider sponsored search settings with multiple slots and the standard model of click through rates that are multiplicatively separable into an advertiser-specific component and a slot-specific component. When similar users have similar advertiser-specific click through rates, our auctions achieve the same near-optimal tradeoff between fairness and quality as in [Chawla and Jagadeesan, 2022]. When similar users can have different advertiser-specific preferences, we show that a preference-based fairness guarantee holds. Finally, we provide a computationally efficient algorithm for computing payments for our auctions as well as those in previous work, resolving another open direction from [Chawla and Jagadeesan, 2022].
BibTeX - Entry
@InProceedings{chawla_et_al:LIPIcs.FORC.2022.4,
author = {Chawla, Shuchi and Rezvan, Rojin and Sauerberg, Nathaniel},
title = {{Individually-Fair Auctions for Multi-Slot Sponsored Search}},
booktitle = {3rd Symposium on Foundations of Responsible Computing (FORC 2022)},
pages = {4:1--4:22},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-226-6},
ISSN = {1868-8969},
year = {2022},
volume = {218},
editor = {Celis, L. Elisa},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2022/16527},
URN = {urn:nbn:de:0030-drops-165272},
doi = {10.4230/LIPIcs.FORC.2022.4},
annote = {Keywords: algorithmic fairness, advertising auctions, and individual fairness}
}
Keywords: |
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algorithmic fairness, advertising auctions, and individual fairness |
Collection: |
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3rd Symposium on Foundations of Responsible Computing (FORC 2022) |
Issue Date: |
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2022 |
Date of publication: |
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15.07.2022 |