  A large fraction of online advertisement is sold via repeated second price
auctions. In these auctions, the reserve price is the main tool for the
auctioneer to boost revenues. In this work, we investigate the following
question: Can changing the reserve prices based on the previous bids improve
the revenue of the auction, taking into account the long-term incentives and
strategic behavior of the bidders? We show that if the distribution of the
valuations is known and satisfies the standard regularity assumptions, then the
optimal mechanism has a constant reserve. However, when there is uncertainty in
the distribution of the valuations, previous bids can be used to learn the
distribution of the valuations and to update the reserve price. We present a
simple, approximately incentive-compatible, and asymptotically optimal dynamic
reserve mechanism that can significantly improve the revenue over the best
static reserve.
  The paper is from July 2014 (our submission to WINE 2014), posted later here
on the arxiv to complement the 1-page abstract in the WINE 2014 proceedings.
