Adaptive bidding for display advertising

Motivated by the emergence of auction-based marketplaces for display ads such as the Right Media Exchange, we study the design of a bidding agent that implements a display advertising campaign by bidding in such a marketplace. The bidding agent must acquire a given number of impressions with a given target spend, when the highest external bid in the marketplace is drawn from an unknown distribution P. The quantity and spend constraints arise from the fact that display ads are usually sold on a CPM basis. We consider both the full information setting, where the winning price in each auction is announced publicly, and the partially observable setting where only the winner obtains information about the distribution; these differ in the penalty incurred by the agent while attempting to learn the distribution. We provide algorithms for both settings, and prove performance guarantees using bounds on uniform closeness from statistics, and techniques from online learning. We experimentally ev...

• Type: Conference
• Year: 2009
• Where: WWW
• Authors: Arpita Ghosh, Benjamin I. P. Rubinstein, Sergei Vassilvitskii, Martin Zinkevich
• Keywords: Bidding Agent, General Terms Algorithms, Internet Technology, Observable Setting, WWW 2009