@conference {17636, title = {On random sampling auctions for digital goods}, booktitle = {Proceedings of the 10th ACM conference on Electronic commerce}, series = {EC {\textquoteright}09}, year = {2009}, month = {2009///}, pages = {187 - 196}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, abstract = {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{\textquoteright}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{\textquoteright}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.}, keywords = {auction, mechanism design, random sampling}, isbn = {978-1-60558-458-4}, doi = {10.1145/1566374.1566402}, url = {http://doi.acm.org/10.1145/1566374.1566402}, author = {Alaei,Saeed and Malekian,Azarakhsh and Srinivasan, Aravind} }