Regret Minimization for Reserve Prices in Second-Price Auctions

We show a regret minimization algorithm for setting the reserve price in a sequence of second-price auctions, under the assumption that all bids are independently drawn from the same unknown and arbitrary distribution. Our algorithm is computationally efficient, and achieves a regret of Õ(√T) in a sequence of T auctions. This holds even when the number of bidders is stochastic with a known distribution.