Revenue optimization against strategic buyers

Mehryar Mohri, Andrés Muñoz Medina

Research output: Contribution to journalConference articlepeer-review


We present a revenue optimization algorithm for posted-price auctions when facing a buyer with random valuations who seeks to optimize his γ-discounted surplus. In order to analyze this problem we introduce the notion of ∈-strategic buyer, a more natural notion of strategic behavior than what has been considered in the past. We improve upon the previous state-of-the-art and achieve an optimal regret bound in O(log T + 1/log(1/γ)) when the seller selects prices from a finite set and provide a regret bound in Õ(√T + T1/4/log(1/γ)) when the prices offered are selected out of the interval [0, 1].

Original languageEnglish (US)
Pages (from-to)2530-2538
Number of pages9
JournalAdvances in Neural Information Processing Systems
StatePublished - 2015
Event29th Annual Conference on Neural Information Processing Systems, NIPS 2015 - Montreal, Canada
Duration: Dec 7 2015Dec 12 2015

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing


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