$Most ReLU Networks Suffer from $\ell^2$ Adversarial Perturbations$

Most ReLU Networks Suffer from $\ell^2$ Adversarial Perturbations

28 October 2020

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Papers citing "Most ReLU Networks Suffer from $\ell^2$ Adversarial Perturbations"

17 / 17 papers shown

Title
Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data Binghui Li Yuanzhi Li OOD 66 3 0 11 Oct 2024
A Simple Explanation for the Existence of Adversarial Examples with Small Hamming Distance A. Shamir Itay Safran Eyal Ronen O. Dunkelman GAN AAML 37 95 0 30 Jan 2019
Are adversarial examples inevitable? Ali Shafahi Wenjie Huang Christoph Studer Soheil Feizi Tom Goldstein SILM 72 283 0 06 Sep 2018
Adversarial examples from computational constraints Sébastien Bubeck Eric Price Ilya P. Razenshteyn AAML 122 233 0 25 May 2018
Adversarially Robust Generalization Requires More Data Ludwig Schmidt Shibani Santurkar Dimitris Tsipras Kunal Talwar Aleksander Madry OOD AAML 152 794 0 30 Apr 2018
Adversarial vulnerability for any classifier Alhussein Fawzi Hamza Fawzi Omar Fawzi AAML 90 251 0 23 Feb 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 243 3,194 0 01 Feb 2018
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text Nicholas Carlini D. Wagner AAML 97 1,083 0 05 Jan 2018
Provable defenses against adversarial examples via the convex outer adversarial polytope Eric Wong J. Zico Kolter AAML 128 1,504 0 02 Nov 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 310 12,117 0 19 Jun 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 131 1,864 0 20 May 2017
Detecting Adversarial Samples from Artifacts Reuben Feinman Ryan R. Curtin S. Shintre Andrew B. Gardner AAML 93 894 0 01 Mar 2017
On the (Statistical) Detection of Adversarial Examples Kathrin Grosse Praveen Manoharan Nicolas Papernot Michael Backes Patrick McDaniel AAML 76 714 0 21 Feb 2017
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 75 3,682 0 08 Feb 2016
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks Nicolas Papernot Patrick McDaniel Xi Wu S. Jha A. Swami AAML 113 3,077 0 14 Nov 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 280 19,107 0 20 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 280 14,961 1 21 Dec 2013