2026-07-22T00:08:36Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:16527 2024-03-06T10:56:13Z ddc:004 open_access

Individually-Fair Auctions for Multi-Slot Sponsored Search Chawla, Shuchi Rezvan, Rojin Sauerberg, Nathaniel algorithmic fairness advertising auctions and individual fairness 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]. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Shuchi Chawla and Rojin Rezvan and Nathaniel Sauerberg 2022 Is Part Of LIPIcs, Volume 218, 3rd Symposium on Foundations of Responsible Computing (FORC 2022) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.FORC.2022.4 urn:nbn:de:0030-drops-165272 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FORC.2022.4 eng https://creativecommons.org/licenses/by/4.0/legalcode