Review for NeurIPS paper: Semi-Supervised Neural Architecture Search

Weaknesses: [Empirical results are not particularly strong] In Table 1, second block SemiNAS (RE) barely outperforms RE. Also in Table 1, third block, SemiNAS outperforms NAO only by 0.12%. While these numbers come from NASBench-101, we all know that empirically, CIFAR-10 accuracy of *any* models and experiments have a standard deviation of about 0.05 - 0.1, and hence I would say there is no improvement between SemiNAS and other baselines. Meanwhile, Table 2 also includes some irrelevant baselines, namely those in the second block, while omits an important baseline. EfficientNet-B0 (Tan and Le, 2019) was found in the same search space of MobileNet-V2, has 390M FLOPs, and has the ImageNet top-1 error of 23.2, which is about the same as 23.5 of SemiNAS. Why is this not reported?