revenue maximization

Algorithmic Information Disclosure in Optimal Auctions
arxiv
Computing Simple Mechanisms: Lift-and-Round over Marginal Reduced Forms
We study revenue maximization in multi-item multi-bidder auctions under the natural item-independence assumption – a classical …
PDF DOI arxiv
Multi-Item Mechanisms without Item-Independence: Learnability via Robustness
We study the sample complexity of learning revenue-optimal multi-item auctions. We obtain the first set of positive results that go …
PDF DOI arXiv
Simple and Approximately Optimal Pricing for Proportional Complementarities
We study a new model of complementary valuations, which we call "proportional complementarities.’’ In contrast to …
PDF DOI arXiv
Learning Multi-Item Auctions with (or without) Samples
We provide algorithms that learn simple auctions whose revenue is approximately optimal in multi-item multi-bidder settings, for a wide …
PDF DOI arXiv
Reducing Bayesian Mechanism Design to Algorithm Design
PDF DOI
Extreme value theorems for optimal multidimensional pricing
We provide near-optimal, polynomial-time algorithms for pricing n items to optimize revenue against a unit-demand buyer whose values …
PDF DOI arXiv
Understanding Incentives: Mechanism Design Becomes Algorithm Design
We provide a computationally efficient black-box reduction from mechanism design to algorithm design in very general settings. …
PDF DOI arXiv