TY - JOUR
T1 - Revenue optimization against strategic buyers
AU - Mohri, Mehryar
AU - Medina, Andrés Muñoz
N1 - Funding Information:
We thank Afshin Rostamizadeh and Umar Syed for useful discussions about the topic of this paper and the NIPS reviewers for their insightful comments. This work was partly funded by NSF IIS-1117591 and NSF CCF-1535987.
PY - 2015
Y1 - 2015
N2 - 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].
AB - 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].
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M3 - Conference article
AN - SCOPUS:84965182140
SN - 1049-5258
VL - 2015-January
SP - 2530
EP - 2538
JO - Advances in Neural Information Processing Systems
JF - Advances in Neural Information Processing Systems
T2 - 29th Annual Conference on Neural Information Processing Systems, NIPS 2015
Y2 - 7 December 2015 through 12 December 2015
ER -