  We give an auction for downward-closed environments that generalizes the
random sampling profit extraction auction for digital goods of Fiat et al.
(2002). The mechanism divides the agents in to a market and a sample using a
biased coin and attempts to extract the optimal revenue from the sample from
the market. The latter step is done with the downward-closed profit extractor
of Ha and Hartline (2012). The auction is a 11-approximation to the envyfree
benchmark in downward-closed permutation environments. This is an improvement
on the previously best known results of 12.5 for matroid and 30.4 for
downward-closed permutation environments that are due to Devanur et al. (2012)
and Ha and Hartline (2012), respectively.
