Generalization analysis with deep ReLU networks for metric and similarity learning

ArXi:2405.06415v2 Announce Type: replace-cross While metric and similarity learning has been extensively studied from several theoretical perspectives, a rigorous understanding of its generalization performance is still lacking. In this paper, we investigate the generalization behavior of metric and similarity learning by exploiting the specific structure of the true metric (i.e., the target function