Fast Core Pricing for Rich Advertising Auctions

Standard ad auction formats do not immediately extend to settings where multiple size configurations and layouts are available to advertisers. In these settings, the sale of web advertising space increasingly resembles a combinatorial auction with complementarities, where truthful auctions such as the Vickrey–Clarke–Groves (VCG) auction can yield unacceptably low revenue. In “Fast Core Pricing for Rich Advertising Auctions,” Niazadeh, Hartline, Immorlica, Khani, and Lucier study and suggest core-selecting auctions, which boost revenue by setting payments so that no group of agents, including the auctioneer, can jointly improve their utilities by switching to a different outcome. Their main result is a combinatorial algorithm that finds an approximate bidder-optimal core point with an almost linear number of calls to the welfare-maximization oracle. This algorithm is faster than previously proposed heuristics in the literature and has theoretical guarantees. By accompanying the theoretical study with an experimental study based on Microsoft Bing Ad Auction data, the authors conclude that core pricing is implementable even for very time-sensitive practical use cases such as real-time online advertising and can yield more revenue than the VCG or generalized second price auction.

VCG under Sybil (False-Name) Attacks - A Bayesian Analysis

VCG is a classical combinatorial auction that maximizes social welfare. However, while the standard single-item Vickrey auction is false-name-proof, a major failure of multi-item VCG is its vulnerability to false-name attacks. This occurs already in the natural bare minimum model in which there are two identical items and bidders are single-minded. Previous solutions to this challenge focused on developing alternative mechanisms that compromise social welfare. We re-visit the VCG auction vulnerability and consider the bidder behavior in Bayesian settings. In service of that we introduce a novel notion, termed the granularity threshold, that characterizes VCG Bayesian resilience to false-name attacks as a function of the bidder type distribution. Using this notion we show a large class of cases in which VCG indeed obtains Bayesian resilience for the two-item single-minded setting.