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.MFCS.2022.5
URN: urn:nbn:de:0030-drops-168031
URL: https://drops.dagstuhl.de/opus/volltexte/2022/16803/
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Vazirani, Vijay V.

Online Bipartite Matching and Adwords (Invited Talk)

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LIPIcs-MFCS-2022-5.pdf (0.7 MB)

Abstract

The purpose of this paper is to give a "textbook quality" proof of the optimal algorithm, called Ranking, for the online bipartite matching problem (OBM) and to highlight its role in matching-based market design. In particular, we discuss a generalization of OBM, called the adwords problem, which has had a significant impact in the ad auctions marketplace.

BibTeX - Entry

@InProceedings{vazirani:LIPIcs.MFCS.2022.5,
  author =	{Vazirani, Vijay V.},
  title =	{{Online Bipartite Matching and Adwords}},
  booktitle =	{47th International Symposium on Mathematical Foundations of Computer Science (MFCS 2022)},
  pages =	{5:1--5:11},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-256-3},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{241},
  editor =	{Szeider, Stefan and Ganian, Robert and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2022/16803},
  URN =		{urn:nbn:de:0030-drops-168031},
  doi =		{10.4230/LIPIcs.MFCS.2022.5},
  annote =	{Keywords: matching-based market design, online algorithms, ad auctions, competitive analysis}
}

Keywords: matching-based market design, online algorithms, ad auctions, competitive analysis
Collection: 47th International Symposium on Mathematical Foundations of Computer Science (MFCS 2022)
Issue Date: 2022
Date of publication: 22.08.2022

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