Venue: ICML 2021 Workshop AML

Reviews:

final_score: rating: Accept
review_content: A Membership Inference Attack (MIA) is the process of determining whether a data sample belongs to a training set of a trained model or not. Lottery Ticket Hypothesis is used to prune the networks to find smaller sub-networks that at least match the performance of the original model in terms of test accuracy in a similar number of iterations. This work shows empirical results for Membership Inference Attacks on Lottery-ticketed Networks. 

Advantages: This work is (claimed to be) the first to empirically show that the lottery ticket networks are equally vulnerable to membership inference attacks.

Suggestions: It is an interesting topic. It would be of great significance to explore more about why the pruned networks are also vulnerable to adversarial attacks. More theoretical analysis may be given.
review_title: This work is (claimed to be) the first to empirically show that the lottery ticket networks are equally vulnerable to membership inference attacks.

Meta-review: This paper showed that lottery ticket networks are equally vulnerable to membership inference attacks. The paper provides several interesting findings.
Decision: Accept (Poster)