In the Neural Architecture Search paper it is stated that the controller RNN (used to generate architectures) had only 35 units in each of its 2 layers. This very small size seems strange to me. My initial explanation was that the authors had too few samples, but they actually used 15,000, which should be enough to train a bigger network. So what in your opinion could be a reason for a smaller network/why making the controller bigger wouldn’t influence the results?