1 code implementation • 27 May 2022 • Miklós Z. Horváth, Mark Niklas Müller, Marc Fischer, Martin Vechev
Whereas most prior work on randomized smoothing focuses on evaluating arbitrary base models approximately under input randomization, the key insight of our work is that decision stump ensembles enable exact yet efficient evaluation via dynamic programming.
1 code implementation • 1 Apr 2022 • Miklós Z. Horváth, Mark Niklas Müller, Marc Fischer, Martin Vechev
Randomized Smoothing (RS) is considered the state-of-the-art approach to obtain certifiably robust models for challenging tasks.
1 code implementation • ICLR 2022 • Miklós Z. Horváth, Mark Niklas Müller, Marc Fischer, Martin Vechev
Randomized Smoothing (RS) is a promising method for obtaining robustness certificates by evaluating a base model under noise.
