Theoretical evidence for adversarial robustness through randomization

Theoretical evidence for adversarial robustness through randomization

4 February 2019

Laurent Meunier

Alexandre Araujo

Cédric Gouy-Pailler

Jamal Atif

Papers citing "Theoretical evidence for adversarial robustness through randomization"

18 / 18 papers shown

Title
A Survey of Neural Network Robustness Assessment in Image Recognition Jie Wang Jun Ai Minyan Lu Haoran Su Dan Yu Yutao Zhang Junda Zhu Jingyu Liu AAML 32 3 0 12 Apr 2024
LipSim: A Provably Robust Perceptual Similarity Metric Sara Ghazanfari Alexandre Araujo Prashanth Krishnamurthy Farshad Khorrami Siddharth Garg 46 5 0 27 Oct 2023
Pre-trained Encoders in Self-Supervised Learning Improve Secure and Privacy-preserving Supervised Learning Hongbin Liu Wenjie Qu Jinyuan Jia Neil Zhenqiang Gong SSL 28 6 0 06 Dec 2022
Enhancing Quantum Adversarial Robustness by Randomized Encodings Weiyuan Gong D. Yuan Weikang Li D. Deng AAML 24 19 0 05 Dec 2022
Causal Information Bottleneck Boosts Adversarial Robustness of Deep Neural Network Hua Hua Jun Yan Xi Fang Weiquan Huang Huilin Yin Wancheng Ge AAML 25 1 0 25 Oct 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
Provably Efficient Black-Box Action Poisoning Attacks Against Reinforcement Learning Guanlin Liu Lifeng Lai AAML 32 34 0 09 Oct 2021
ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients Alessandro Cappelli Julien Launay Laurent Meunier Ruben Ohana Iacopo Poli AAML 29 4 0 06 Jul 2021
Learning distinct features helps, provably Firas Laakom Jenni Raitoharju Alexandros Iosifidis Moncef Gabbouj MLT 36 6 0 10 Jun 2021
Mixed Nash Equilibria in the Adversarial Examples Game Laurent Meunier M. Scetbon Rafael Pinot Jamal Atif Y. Chevaleyre AAML 23 29 0 13 Feb 2021
Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations Jinyuan Jia Binghui Wang Xiaoyu Cao Hongbin Liu Neil Zhenqiang Gong 21 24 0 15 Nov 2020
A Le Cam Type Bound for Adversarial Learning and Applications Qiuling Xu Kevin Bello Jean Honorio AAML 23 1 0 01 Jul 2020
Calibrated Surrogate Losses for Adversarially Robust Classification Han Bao Clayton Scott Masashi Sugiyama 29 45 0 28 May 2020
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness Ahmadreza Jeddi M. Shafiee Michelle Karg C. Scharfenberger A. Wong OOD AAML 72 63 0 02 Mar 2020
Towards Rapid and Robust Adversarial Training with One-Step Attacks Leo Schwinn René Raab Björn Eskofier AAML 33 6 0 24 Feb 2020
A unified view on differential privacy and robustness to adversarial examples Rafael Pinot Florian Yger Cédric Gouy-Pailler Jamal Atif AAML 21 17 0 19 Jun 2019
Adversarial examples from computational constraints Sébastien Bubeck Eric Price Ilya P. Razenshteyn AAML 65 230 0 25 May 2018
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 317 5,847 0 08 Jul 2016