Efficient Empirical Revenue Maximization in Single-Parameter Auction Environments

STOC, pp. 856-868, 2017.

Cited by: 46|Bibtex|Views37|DOI:https://doi.org/10.1145/3055399.3055427
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Other Links: dblp.uni-trier.de|dl.acm.org|academic.microsoft.com|arxiv.org

Abstract:

We present a polynomial-time algorithm that, given samples from the unknown valuation distribution of each bidder, learns an auction that approximately maximizes the auctioneer's revenue in a variety of single-parameter auction environments including matroid environments, position environments, and the public project environment. The valu...More

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