scholar.google.com › citations
May 15, 2020 · As a certified defensive technique, randomized smoothing has received considerable attention due to its scalability to large datasets and neural networks.
Bibliographic details on Towards Assessment of Randomized Mechanisms for Certifying Adversarial Robustness.
Towards Assessment of Randomized Smoothing Mechanisms for Certifying Adversarial Robustness · Tianhang Zheng, Di Wang, +1 author. Jinhui Xu · Published 15 May ...
As a certified defensive technique, randomized smoothing has received considerable attention due to its scalability to large datasets and neural networks.
Our analysis reveals that smoothing with Gaussian noise naturally induces certifiable robustness under the `2 norm. We suspect that other, as-yet-unknown noise ...
Missing: Assessment | Show results with:Assessment
We show how to turn any classifier that classifies well under Gaussian noise into a new classifier that is certifiably robust to adversarial perturba-.
Missing: Assessment | Show results with:Assessment
This paper investigates the theory of robustness against adversarial attacks. It focuses on the family of randomization techniques that consist in injecting ...
Missing: Assessment | Show results with:Assessment
In this work, we take first steps towards separating robustness analysis from the choice of robustness threshold and norm. We propose robustness curves as a ...
Dec 20, 2019 · This work derives certified robustness for top-k predictions based on randomized smoothing, which turns any classifier to a new classifier ...
People also ask
What is adversarial robustness of AI models?
Are adversarial robustness and common perturbation robustness independent attributes?
What is randomized smoothing?
Aug 2, 2022 · This paper investigates the theory of robustness against adversarial attacks. We focus on randomized classifiers (ie classifiers that output random variables)
Missing: Assessment | Show results with:Assessment