Learning theory and algorithms for revenue optimization in second-price auctions with reserve

Mehryar Mohri, Andres Muñoz Medina

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

2014 Second-price auctions with reserve play a critical role in the revenue of modem search engine and popular online sites since the revenue of these companies often directly depends on the outcome of such auctions. The choice of the reserve price is the main mechanism through which the auction revenue can be influenced in these electronic markets. We cast the problem of selecting the reserve price to optimize revenue as a learning problem and present a full theoretical analysis dealing with the complex properties of the corresponding loss function. We further give novel algorithms for solving this problem and report the results of several experiments demonstrating their effectiveness.

Original languageEnglish (US)
Title of host publication31st International Conference on Machine Learning, ICML 2014
PublisherInternational Machine Learning Society (IMLS)
Pages443-451
Number of pages9
Volume1
ISBN (Print)9781634393973
StatePublished - 2014
Event31st International Conference on Machine Learning, ICML 2014 - Beijing, China
Duration: Jun 21 2014Jun 26 2014

Other

Other31st International Conference on Machine Learning, ICML 2014
CountryChina
CityBeijing
Period6/21/146/26/14

Fingerprint

Modems
Search engines
Industry
Experiments

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Software

Cite this

Mohri, M., & Medina, A. M. (2014). Learning theory and algorithms for revenue optimization in second-price auctions with reserve. In 31st International Conference on Machine Learning, ICML 2014 (Vol. 1, pp. 443-451). International Machine Learning Society (IMLS).

Learning theory and algorithms for revenue optimization in second-price auctions with reserve. / Mohri, Mehryar; Medina, Andres Muñoz.

31st International Conference on Machine Learning, ICML 2014. Vol. 1 International Machine Learning Society (IMLS), 2014. p. 443-451.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Mohri, M & Medina, AM 2014, Learning theory and algorithms for revenue optimization in second-price auctions with reserve. in 31st International Conference on Machine Learning, ICML 2014. vol. 1, International Machine Learning Society (IMLS), pp. 443-451, 31st International Conference on Machine Learning, ICML 2014, Beijing, China, 6/21/14.
Mohri M, Medina AM. Learning theory and algorithms for revenue optimization in second-price auctions with reserve. In 31st International Conference on Machine Learning, ICML 2014. Vol. 1. International Machine Learning Society (IMLS). 2014. p. 443-451
Mohri, Mehryar ; Medina, Andres Muñoz. / Learning theory and algorithms for revenue optimization in second-price auctions with reserve. 31st International Conference on Machine Learning, ICML 2014. Vol. 1 International Machine Learning Society (IMLS), 2014. pp. 443-451
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