Incentive-compatible online auctions for digital goods
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Adaptive limited-supply online auctions
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Online learning in online auctions
Theoretical Computer Science - Special issue: Online algorithms in memoriam, Steve Seiden
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
From optimal limited to unlimited supply auctions
Proceedings of the 6th ACM conference on Electronic commerce
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Optimal mechanism design and money burning
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Online auctions and generalized secretary problems
ACM SIGecom Exchanges
Reducing mechanism design to algorithm design via machine learning
Journal of Computer and System Sciences
On random sampling auctions for digital goods
Proceedings of the 10th ACM conference on Electronic commerce
Revenue maximization with a single sample
Proceedings of the 11th ACM conference on Electronic commerce
On the competitive ratio of the random sampling auction
WINE'05 Proceedings of the First international conference on Internet and Network Economics
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We study online profit-maximizing auctions for digital goods with adversarial bid selection and uniformly random arrivals; in this sense, our model lies at the intersection of prior-free mechanism design and secretary problems. Our goal is to design auctions that are constant competitive with F(2). We give a generic reduction that transforms any offline auction to an online one with only a loss of a factor of 2 in the competitive ratio. We also present some natural auctions, both randomized and deterministic, and study their competitive ratio. Our analysis reveals some interesting connections of one of these auctions with RSOP.