Certified Robustness via Randomized Smoothing over Multiplicative Parameters.
Nikita Valerevich Muravev, Aleksandr Petiushko · arXiv (Cornell University) · 2021
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.