Hanbin Hong

UniCR: Universally Approximated Certified Robustness via Randomized Smoothing

"We study certified robustness of machine learning classifiers against adversarial perturbations. In particular, we propose the first universally approximated certified robustness (UniCR) framework, which can approximate the robustness certification of \emph{any} input on \emph{any} classifier again…