- Angus Galloway
- Anna Golubeva
- Graham William Taylor
NeurIPS Workshop on Security in Machine Learning (2018)
We analyze the adversarial examples problem in terms of a model’s fault tolerance with respect to its input. Whereas previous work focuses on arbitrarily strict threat models, i.e., -perturbations, we consider arbitrary valid inputs and propose an information-based characteristic for evaluating tolerance to diverse input faults.
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