We consider a monopolist seller with n heterogeneous items, facing a single buyer. The
buyer has a value for each item drawn independently according to (non-identical) …

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 …

We survey the main results from [Dütting, Kesselheim, and Lucier 2020]: 1 a simple posted-
price mechanism for subadditive combinatorial auctions with m items that achieves an O (log …

We consider the sample complexity of revenue maximization for multiple bidders in
unrestricted multi-dimensional settings. Specifically, we study the standard model of additive …

We provide algorithms that learn simple auctions whose revenue is approximately optimal in
multi-item multi-bidder settings, for a wide range of bidder valuations including unit-demand …

Buying and selling of data online has increased substantially over the last few years.
Several frameworks have already been proposed that study query pricing in theory and …

We study the sample complexity of learning revenue-optimal multi-item auctions. We obtain
the first set of positive results that go beyond the standard but unrealistic setting of item …

We study the problem of designing mechanisms when agents' valuation functions are drawn
from unknown and correlated prior distributions. In particular, we are given a prior …