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[D] How to , concretly, measure a model’s robustness against adversarial/perturbations examples? … I mean concretly.

We know that we can measure a model’s robustness to perturbation by applying perturbation to training points and checking if the outputs are the same:

The lp ball around an image is said to be the adversarial ball, and a network is said to be E-robust around x if every point in the adversarial ball around x classifies the same. source, Part 3

But how is this done concretely?

submitted by /u/data-soup
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.