  We consider the practical and classical setting where the seller is using an
exploration stage to learn the value distributions of the bidders before
running a revenue-maximizing auction in a exploitation phase. In this two-stage
process, we exhibit practical, simple and robust strategies with large utility
uplifts for the bidders. We quantify precisely the seller revenue against
non-discounted buyers, complementing recent studies that had focused on
impatient/heavily discounted buyers. We also prove the robustness of these
shading strategies to sample approximation error of the seller, to bidder's
approximation error of the competition and to possible change of the
mechanisms.
