364 citations · 942 across the 15 of their papers we have counts for
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cs.CR2019
Adversarial Vulnerability Bounds for Gaussian Process Classification
Michael Thomas Smith, Kathrin Grosse, Michael Backes +1
Machine learning (ML) classification is increasingly used in safety-critical systems. Protecting ML classifiers from adversarial examples is crucial. We propose that the main threa…
cs.CR2019
On the security relevance of weights in deep learning
Kathrin Grosse, Thomas A. Trost, Marius Mosbach +2
Recently, a weight-based attack on stochastic gradient descent inducing overfitting has been proposed. We show that the threat is broader: A task-independent permutation on the ini…