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Poster
Learning Prices for Repeated Auctions with Strategic Buyers
Kareem Amin · Afshin Rostamizadeh · Umar Syed

Thu Dec 05 07:00 PM -- 11:59 PM (PST) @ Harrah's Special Events Center, 2nd Floor #None

Inspired by real-time ad exchanges for online display advertising, we consider the problem of inferring a buyer's value distribution for a good when the buyer is repeatedly interacting with a seller through a posted-price mechanism. We model the buyer as a strategic agent, whose goal is to maximize her long-term surplus, and we are interested in mechanisms that maximize the seller's long-term revenue. We present seller algorithms that are no-regret when the buyer discounts her future surplus --- i.e. the buyer prefers showing advertisements to users sooner rather than later. We also give a lower bound on regret that increases as the buyer's discounting weakens and shows, in particular, that any seller algorithm will suffer linear regret if there is no discounting.

Author Information

Kareem Amin (University of Pennsylvania)
Afshin Rostamizadeh (Google Research)
Umar Syed (Google Research)

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