We study the classic mathematical economics problem of Bayesian optimal mechanism
design where a principal aims to optimize expected revenue when allocating resources to …

We study anonymous posted price mechanisms for combinatorial auctions in a Bayesian
framework. In a posted price mechanism, item prices are posted, then the consumers …

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) …

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 …

This paper studies the optimal pricing strategy of a hotel that establishes an online
distribution channel through cooperation with an online travel agency (OTA). The OTA …

Abstract Systems wherein strategic agents compete for limited resources are ubiquitous: the
economy, computer networks, social networks, congestion networks, nature, etc. Assuming …

We provide a reduction from revenue maximization to welfare maximization in
multidimensional Bayesian auctions with arbitrary-possibly combinatorial-feasibility …

Deep neural networks (DNNs) exploit many layers and a large number of parameters to
achieve excellent performance. The training process of DNN models generally handles …

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 …