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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
lpball around an image is said to be the adversarial ball, and a network is said to beE-robustaroundxif every point in the adversarial ball aroundxclassifies the same. source, Part 3
But how is this done concretely?
submitted by /u/data-soup
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