%0 Conference Paper
%B Proceedings of the 10th ACM conference on Electronic commerce
%D 2009
%T On random sampling auctions for digital goods
%A Alaei,Saeed
%A Malekian,Azarakhsh
%A Srinivasan, Aravind
%K auction
%K mechanism design
%K random sampling
%X In the context of auctions for digital goods, an interesting Random Sampling Optimal Price auction (RSOP) has been proposed by Goldberg, Hartline and Wright; this leads to a truthful mechanism. Since random sampling is a popular approach for auctions that aims to maximize the seller's revenue, this method has been analyzed further by Feige, Flaxman, Hartline and Kleinberg, who have shown that it is 15-competitive in the worst case -- which is substantially better than the previously proved bounds but still far from the conjectured competitive ratio of 4. In this paper, we prove that RSOP is indeed 4-competitive for a large class of instances in which the number λ of bidders receiving the item at the optimal uniform price, is at least 6. We also show that it is 4.68 competitive for the small class of remaining instances thus leaving a negligible gap between the lower and upper bound. Furthermore, we develop a robust version of RSOP -- one in which the seller's revenue is, with high probability, not much below its mean -- when the above parameter λ grows large. We employ a mix of probabilistic techniques and dynamic programming to compute these bounds.
%B Proceedings of the 10th ACM conference on Electronic commerce
%S EC '09
%I ACM
%C New York, NY, USA
%P 187 - 196
%8 2009///
%@ 978-1-60558-458-4
%G eng
%U http://doi.acm.org/10.1145/1566374.1566402
%R 10.1145/1566374.1566402