v1v2 (latest)

Scaleable input gradient regularization for adversarial robustness

27 May 2019

Papers citing "Scaleable input gradient regularization for adversarial robustness"

48 / 48 papers shown

Title
MIRACLE3D: Memory-efficient Integrated Robust Approach for Continual Learning on Point Clouds via Shape Model Construction Hossein Resani B. Nasihatkon 3DV 421 0 0 08 Oct 2024
Is Adversarial Training with Compressed Datasets Effective? Tong Chen Raghavendra Selvan AAML 146 0 0 08 Feb 2024
Nash Equilibria, Regularization and Computation in Optimal Transport-Based Distributionally Robust Optimization Soroosh Shafieezadeh-Abadeh Liviu Aolaritei Florian Dorfler Daniel Kuhn 127 21 0 07 Mar 2023
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers Hadi Salman Greg Yang Jungshian Li Pengchuan Zhang Huan Zhang Ilya P. Razenshteyn Sébastien Bubeck AAML 78 551 0 09 Jun 2019
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle Dinghuai Zhang Tianyuan Zhang Yiping Lu Zhanxing Zhu Bin Dong AAML 113 361 0 02 May 2019
Adversarial Training for Free! Ali Shafahi Mahyar Najibi Amin Ghiasi Zheng Xu John P. Dickerson Christoph Studer L. Davis Gavin Taylor Tom Goldstein AAML 134 1,251 0 29 Apr 2019
The LogBarrier adversarial attack: making effective use of decision boundary information Chris Finlay Aram-Alexandre Pooladian Adam M. Oberman AAML 67 25 0 25 Mar 2019
L 1-norm double backpropagation adversarial defense Ismaïla Seck Gaëlle Loosli S. Canu GAN AAML 34 4 0 05 Mar 2019
On Evaluating Adversarial Robustness Nicholas Carlini Anish Athalye Nicolas Papernot Wieland Brendel Jonas Rauber Dimitris Tsipras Ian Goodfellow Aleksander Madry Alexey Kurakin ELM AAML 98 906 0 18 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 158 2,051 0 08 Feb 2019
Feature Denoising for Improving Adversarial Robustness Cihang Xie Yuxin Wu Laurens van der Maaten Alan Yuille Kaiming He 110 912 0 09 Dec 2018
Robustness via curvature regularization, and vice versa Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi J. Uesato P. Frossard AAML 82 319 0 23 Nov 2018
Semidefinite relaxations for certifying robustness to adversarial examples Aditi Raghunathan Jacob Steinhardt Percy Liang AAML 100 439 0 02 Nov 2018
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability Kai Y. Xiao Vincent Tjeng Nur Muhammad (Mahi) Shafiullah Aleksander Madry AAML OOD 41 201 0 09 Sep 2018
Limitations of the Lipschitz constant as a defense against adversarial examples Todd P. Huster C. Chiang R. Chadha AAML 47 84 0 25 Jul 2018
Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark Cody Coleman Daniel Kang Deepak Narayanan Luigi Nardi Tian Zhao Jian Zhang Peter Bailis K. Olukotun Christopher Ré Matei A. Zaharia 53 117 0 04 Jun 2018
Scaling provable adversarial defenses Eric Wong Frank R. Schmidt J. H. Metzen J. Zico Kolter AAML 78 450 0 31 May 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 106 1,782 0 30 May 2018
Adversarially Robust Training through Structured Gradient Regularization Kevin Roth Aurelien Lucchi Sebastian Nowozin Thomas Hofmann 65 23 0 22 May 2018
Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization Daniel Jakubovitz Raja Giryes AAML 58 210 0 23 Mar 2018
Adversarial Logit Pairing Harini Kannan Alexey Kurakin Ian Goodfellow AAML 98 628 0 16 Mar 2018
Sensitivity and Generalization in Neural Networks: an Empirical Study Roman Novak Yasaman Bahri Daniel A. Abolafia Jeffrey Pennington Jascha Narain Sohl-Dickstein AAML 95 441 0 23 Feb 2018
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks J. Uesato Brendan O'Donoghue Aaron van den Oord Pushmeet Kohli AAML 160 605 0 15 Feb 2018
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks Yusuke Tsuzuku Issei Sato Masashi Sugiyama AAML 105 309 0 12 Feb 2018
First-order Adversarial Vulnerability of Neural Networks and Input Dimension Carl-Johann Simon-Gabriel Yann Ollivier Léon Bottou Bernhard Schölkopf David Lopez-Paz AAML 79 48 0 05 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
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach Tsui-Wei Weng Huan Zhang Pin-Yu Chen Jinfeng Yi D. Su Yupeng Gao Cho-Jui Hsieh Luca Daniel AAML 83 468 0 31 Jan 2018
Certified Defenses against Adversarial Examples Aditi Raghunathan Jacob Steinhardt Percy Liang AAML 113 969 0 29 Jan 2018
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models Wieland Brendel Jonas Rauber Matthias Bethge AAML 69 1,350 0 12 Dec 2017
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients A. Ross Finale Doshi-Velez AAML 154 683 0 26 Nov 2017
Provable defenses against adversarial examples via the convex outer adversarial polytope Eric Wong J. Zico Kolter AAML 128 1,504 0 02 Nov 2017
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 160 2,159 0 21 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 315 12,131 0 19 Jun 2017
Gradient descent GAN optimization is locally stable Vaishnavh Nagarajan J. Zico Kolter GAN 86 348 0 13 Jun 2017
Stabilizing Training of Generative Adversarial Networks through Regularization Kevin Roth Aurelien Lucchi Sebastian Nowozin Thomas Hofmann GAN 64 446 0 25 May 2017
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation Matthias Hein Maksym Andriushchenko AAML 115 512 0 23 May 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 131 1,864 0 20 May 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 177 2,728 0 19 May 2017
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning Takeru Miyato S. Maeda Masanori Koyama S. Ishii GAN 151 2,738 0 13 Apr 2017
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Zhuowen Tu Kaiming He 522 10,347 0 16 Nov 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 266 8,579 0 16 Aug 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 545 5,909 0 08 Jul 2016
Identity Mappings in Deep Residual Networks Kaiming He Xinming Zhang Shaoqing Ren Jian Sun 354 10,192 0 16 Mar 2016
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
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 115 3,967 0 24 Nov 2015
A Unified Gradient Regularization Family for Adversarial Examples Chunchuan Lyu Kaizhu Huang Hai-Ning Liang AAML 68 209 0 19 Nov 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 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 282 14,961 1 21 Dec 2013