Certified Robustness via Randomized Smoothing over Multiplicative Parameters

06/28/2021

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by   Nikita Muravev, et al.

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We propose a novel approach of randomized smoothing over multiplicative parameters. Using this method we construct certifiably robust classifiers with respect to a gamma-correction perturbation and compare the result with classifiers obtained via Gaussian smoothing. To the best of our knowledge it is the first work concerning certified robustness against the multiplicative gamma-correction transformation.