Designing an incentive compatible auction that maximizes expected revenue is an intricate
task. The single-item case was resolved in a seminal piece of work by Myerson in 1981 …

We provide a duality-based framework for revenue maximization in a multiple-good
monopoly. Our framework shows that every optimal mechanism has a certificate of …

The field of optimal mechanism design enjoys a beautiful and well-developed theory, as well
as several killer applications. Rules of thumb produced by the field influence everything from …

A principal wishes to screen an agent along several dimensions of private information
simultaneously. The agent has quasilinear preferences that are additively separable across …

This paper develops a general approach, rooted in statistical learning theory, to learning an
approximately revenue-maximizing auction from data. We introduce t-level auctions to …

Maximizing the revenue from selling more than one good (or item) to a single buyer is a
notoriously difficult problem, in stark contrast to the one-good case. For two goods, we show …

We present a general framework for proving polynomial sample complexity bounds for the
problem of learning from samples the best auction in a class of “simple” auctions. Our …

We provide a unified view of many recent developments in Bayesian mechanism design,
including the black-box reductions of Cai et. al., simple auctions for additive buyers, and …

We provide simple and approximately revenue-optimal mechanisms in the multi-item multi-
bidder settings. We unify and improve all previous results, as well as generalize the results …

We study the revenue maximization problem of a seller with n heterogeneous items for sale
to a single buyer whose valuation function for sets of items is unknown and drawn from …