We would first like to thank the reviewers for especially detailed and high quality reviews. That said, this may have had the opposite effect of being confusing. Simple blurs are another example of a semigroup action on the whole signal. Resource Efficient Image Classification" (Huang et al., 2018) are also very interesting and have now been added to our Indeed, in Dilated Residual Networks (Y u et al., 2017), there is no bandlimiting at all (we Moreover, maybe the use of dilated convolutions in the end "does Furthermore, in related works there are no "standard ImageNet, but in Feature Pyramid Networks, the authors look at COCO. We do intend to extend the current work to other domains and to other kinds of semigroup action.

Peer review is the foundation of scientific publication, and the task of reviewing has long been seen as a cornerstone of professional service. However, the massive growth in the field of machine learning has put this community benefit under stress, threatening both the sustainability of an effective review process and the overall progress of the field. In this position paper, we argue that a tragedy of the commons outcome may be avoided by emphasizing the professional aspects of this service. In particular, we propose a rubric to hold reviewers to an objective standard for review quality. In turn, we also propose that reviewers be given appropriate incentive. As one possible such incentive, we explore the idea of financial compensation on a per-review basis. We suggest reasonable funding models and thoughts on long term effects.