# Approximate Revenue Maximization in Interdependent Value Settings

arXiv: https://arxiv.org/abs/1408.4424 · HTML: https://mlsanity.com/paper/1408.4424/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Aug 2014.

## Built on by (most cited first, 1 of 1)

- [Cursed yet Satisfied Agents](https://mlsanity.com/paper/2104.00835/) (2021)

## Abstract (arXiv)

We study revenue maximization in settings where agents' values are interdependent: each agent receives a signal drawn from a correlated distribution and agents' values are functions of all of the signals. We introduce a variant of the generalized VCG auction with reserve prices and random admission, and show that this auction gives a constant approximation to the optimal expected revenue in matroid environments. Our results do not require any assumptions on the signal distributions, however, they require the value functions to satisfy a standard single-crossing property and a concavity-type condition.