Review for NeurIPS paper: Adversarial Robustness of Supervised Sparse Coding

Additional Feedback: Overall, the work achieves new and interesting theoretical results for the model being studied. My main worry is the lack of experimental results on the encoder gap for datasets beyond MNIST, especially given that the size/existence of the encoder gap is crucial to the theoretical results and is an assumption made in the theoretical claims. Thus, I would highly recommend at least evaluating the encoder gap for other (more complex than MNIST) datasets. Many techniques that work well on MNIST may not work on other datasets due to MNIST's relative simplicity. For example, a network that binarizes pixel values (converts everything below 0.5 to 0, everything above to 1) and then classifies the result is quite adversarially robust, but the same technique will not work for more complex datasets.