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Learning Auctions with Robust Incentive Guarantees
We study the problem of learning Bayesian-optimal revenue-maximizing auctions.
On the Pseudo-Dimension of Nearly Optimal Auctions
This paper develops a general approach, rooted in statistical learning theory, to learning an approximately revenue-maximizing auction from data.
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