Venue: ICML 2021 Workshop AML

Reviews:

final_score: rating: Accept
review_content: The authors proposed SmoothnMix which trains neural networks by using convex combinations of adversarial perturbations.  By adding a mixup loss as a regularization term, the confidence of over-confident samples can be calibrated. The experimental results show that there is a small but effective improvement by adding this regularization term.

A typo in line 24, "the smoothed classifiers offer is a direct ..."
review_title: A novel adversarial training scheme for improving certified robustness

Meta-review: This paper proposed SmoothnMix which trains neural networks by using convex combinations of adversarial perturbations. The paper is suitable for the workshop.
Decision: Accept (Poster)