Simple versus optimal mechanisms
Proceedings of the 10th ACM conference on Electronic commerce
Multi-parameter mechanism design and sequential posted pricing
Proceedings of the forty-second ACM symposium on Theory of computing
Budget constrained auctions with heterogeneous items
Proceedings of the forty-second ACM symposium on Theory of computing
Revenue maximization with a single sample
Proceedings of the 11th ACM conference on Electronic commerce
The power of randomness in bayesian optimal mechanism design
Proceedings of the 11th ACM conference on Electronic commerce
On optimal multidimensional mechanism design
ACM SIGecom Exchanges
Bayesian Combinatorial Auctions: Expanding Single Buyer Mechanisms to Many Buyers
FOCS '11 Proceedings of the 2011 IEEE 52nd Annual Symposium on Foundations of Computer Science
Prior-free auctions with ordered bidders
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
Selling in Exclusive Markets: Some Observations on Prior-Free Mechanism Design
ACM Transactions on Economics and Computation - Special Issue on Algorithmic Game Theory
Near-optimal multi-unit auctions with ordered bidders
Proceedings of the fourteenth ACM conference on Electronic commerce
Prior-independent mechanisms for scheduling
Proceedings of the forty-fifth annual ACM symposium on Theory of computing
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In a unit-demand multi-unit multi-item auction, an auctioneer is selling a collection of different items to a set of agents each interested in buying at most unit. Each agent has a different private value for each of the items. We consider the problem of designing a truthful auction that maximizes the auctioneer's profit in this setting. Previously, there has been progress on this problem in the setting in which each value is drawn from a known prior distribution. Specifically, it has been shown how to design auctions tailored to these priors that achieve a constant factor approximation ratio [2, 5]. In this paper, we present a prior-independent auction for this setting. This auction is guaranteed to achieve a constant fraction of the optimal expected profit for a large class of, so called, "regular" distributions, without specific knowledge of the distributions.