364 citations · 942 across the 15 of their papers we have counts for
3 papers · 1 filter
Adversarial Examples and Metrics
Nico Döttling, Kathrin Grosse, Michael Backes +1
Adversarial examples are a type of attack on machine learning (ML) systems which cause misclassification of inputs. Achieving robustness against adversarial examples is crucial to…
How many winning tickets are there in one DNN?
Kathrin Grosse, Michael Backes
The recent lottery ticket hypothesis proposes that there is one sub-network that matches the accuracy of the original network when trained in isolation. We show that instead each n…
Backdoor Smoothing: Demystifying Backdoor Attacks on Deep Neural Networks
Kathrin Grosse, Taesung Lee, Battista Biggio +3
Backdoor attacks mislead machine-learning models to output an attacker-specified class when presented a specific trigger at test time. These attacks require poisoning the training…