Extensions and limitations of randomized smoothing for robustness guarantees

7 June 2020

Papers citing "Extensions and limitations of randomized smoothing for robustness guarantees"

10 / 10 papers shown

Title
Certified Policy Smoothing for Cooperative Multi-Agent Reinforcement Learning Ronghui Mu Wenjie Ruan Leandro Soriano Marcolino Gaojie Jin Q. Ni 47 5 0 22 Dec 2022
CARE: Certifiably Robust Learning with Reasoning via Variational Inference Jiawei Zhang Linyi Li Ce Zhang Bo Li AAML OOD 48 8 0 12 Sep 2022
Double Sampling Randomized Smoothing Linyi Li Jiawei Zhang Tao Xie Bo Li AAML 19 23 0 16 Jun 2022
Towards Evading the Limits of Randomized Smoothing: A Theoretical Analysis Raphael Ettedgui Alexandre Araujo Rafael Pinot Y. Chevaleyre Jamal Atif AAML 34 3 0 03 Jun 2022
Randomized Smoothing under Attack: How Good is it in Pratice? Thibault Maho Teddy Furon Erwan Le Merrer AAML 19 10 0 28 Apr 2022
ε-weakened Robustness of Deep Neural Networks Pei Huang Yuting Yang Minghao Liu Fuqi Jia Feifei Ma Jian Zhang AAML 27 18 0 29 Oct 2021
Certified Robustness via Randomized Smoothing over Multiplicative Parameters of Input Transformations Nikita Muravev Aleksandr Petiushko AAML 21 7 0 28 Jun 2021
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Bo Li AAML 38 128 0 09 Sep 2020
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks Akhilan Boopathy Tsui-Wei Weng Pin-Yu Chen Sijia Liu Luca Daniel AAML 110 138 0 29 Nov 2018
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 251 1,842 0 03 Feb 2017