d0f5edad9ac19abed9e235c0fe0aa59f-AuthorFeedback.pdf

We thank the reviewer for providing constructive feedback and suggestions. By now, the number of papers (and books!) using these two parametrizations is In this view, the specific regime in which our rates are better is not really important. Our final comments on the bias of the community towards "weak assumptions" was So, we are happy that the reviewer engaged with us in this discussion! "strong" is the case of zero Bayes error w.r.t. the square loss: It is completely a problem-dependent judgment rather Instead, we just consider it an interesting setting that researchers have ignored for a long time. Moreover, we do plan to extend the results we presented to smooth classification losses, as the squared hinge loss.