Just as important, however, is that the representation must simultaneously make the source and target domains look as similar to one another as possible.
if the labeling function f is the same on the source and target domains, then for every h ∈ H, we can provably bound the error of h on the target domain by its error on the source domain plus a measure of the distance between D S and D T : where the variation divergence d 1 is given by where B is the set of measurable sets under D and D (Ben-David et al.