Reviewer # 1

We thank the reviewers for their positive feedbacks and valuable suggestions. We address their comments below. In short, "pruning-at-initialization" methods have the advantage of less overhead at training time. In contrast, our approach can be adopted even when the model is trained without any consideration of pruning. However, we think providing a self-sufficient proof in the current form is not a bad idea, either.