Reviews: Neural Architecture Optimization

I think the optimization approach proposed in the paper is novel enough to justify the high score, and that the experimental evaluation is sufficient to show that the optimization method is doing something sensible. I also think that the new experiments from the rebuttal will improve the paper, and will help address some of the concerns raised in the original reviews. Comparison with related work: The experiments in this paper show state-of-the-art results. However, in the original submission, it was difficult to tell the extent to which quality and sample efficiency improvements over NASNet/AmoebaNet were coming from the optimization algorithm, as opposed to search space improvements or longer training times. The authors directly address both points in their rebuttal, and I believe the experiments they mention will help explain where the efficiency improvements come from.