We thank all the reviewers for the valuable comments and suggestions. Besides, we indeed use dropout as in NoisyStudent (the paper you mentioned) to help generalization. We also combine SemiNAS with other NAS algorithm (e.g., Regularized Evolution) and We will add such experiments in the new version. SemiNAS (RE) consuming 2000 pairs to compare with RE under the same number of queries, and it achieves 94.03% CIFAR-10, there exist some differences. It runs each model for 3 times and collect the 3 results to reduce the variance.

We thank all of the reviewers for their valuable comments and suggestions. We have replaced "Iterations" with "Time" in Figure 1 R2: W all-clock time comparison and # of potential functions being evaluated. Please refer to Figure 3. Additionally, R2: Are there problems on which vanilla Gibbs would be prohibitively expensive? R2: Are there problems on which Poisson-Gibbs might fail? Empirically, we did not find a poor initialization issue for Poisson-Gibbs.

We will add more details of the results in the final version.