Computing Simple Mechanisms: Lift-and-Round over Marginal Reduced Forms
Yang Cai, Argyris Oikonomou, Mingfei Zhao

TL;DR
This paper presents a polynomial-time algorithm for approximating optimal revenue in multi-item auctions with XOS bidders, using novel representations and a lift-and-round technique to find simple, near-optimal mechanisms.
Contribution
It introduces the first polynomial-time algorithm for XOS valuations, utilizing new mechanism representations and a lift-and-round method to efficiently approximate optimal revenue.
Findings
Achieved $O(1)$-approximation for XOS bidders.
Designed mechanisms are either posted price or two-part tariffs.
Extended results to sample-based approximation using bidder distribution samples.
Abstract
We study revenue maximization in multi-item multi-bidder auctions under the natural item-independence assumption - a classical problem in Multi-Dimensional Bayesian Mechanism Design. One of the biggest challenges in this area is developing algorithms to compute (approximately) optimal mechanisms that are not brute-force in the size of the bidder type space, which is usually exponential in the number of items in multi-item auctions. Unfortunately, such algorithms were only known for basic settings of our problem when bidders have unit-demand [CHMS10,CMS15] or additive valuations [Yao15]. In this paper, we significantly improve the previous results and design the first algorithm that runs in time polynomial in the number of items and the number of bidders to compute mechanisms that are -approximations to the optimal revenue when bidders have XOS valuations, resolving an open…
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Taxonomy
TopicsAuction Theory and Applications · Consumer Market Behavior and Pricing · Law, Economics, and Judicial Systems
