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 Qscript(√T) in a sequence of T auctions. This holds even when the number of bidders is stochastic with a known distribution.

Regret Minimization for Reserve Prices in Second-Price Auctions

GENTILE, CLAUDIO;
2015-01-01

Abstract

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 Qscript(√T) in a sequence of T auctions. This holds even when the number of bidders is stochastic with a known distribution.
2015
Prediction theory; semi-supervised learning; sequential analysis; statistical learning; Information Systems; Computer Science Applications1707 Computer Vision and Pattern Recognition; Library and Information Sciences
Cesa Bianchi, N.; Gentile, Claudio; Mansour, Y.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2044974
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