Theory-Inspired Path-Regularized Differential Network Architecture Search (Supplementary File)

Then Appendix C gives the proofs of the main results in Sec. 3, namely Theorem 1, by first introducing auxiliary theories Due to space limitation, we defer more experimental results and details to this appendix. Due to the high training cost, we fix two regularization parameters and then investigate the third one. This testifies the robustness of PR-DARTS to regularization parameters.Figure 3: Effects of regularization parameters Here we first display the selected reduction cell on CIRAR10 in Figure 1 (a). Next, we also report the average gate activate probability in the normal and reduction cells in Figure 1 (b). At the beginning of the search, we initialize the activation probability of each gate to be one.