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Is PGD-Adversarial Training Necessary? Alternative Training via a Soft-Quantization Network with Noisy-Natural Samples Only

10 October 2018

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Papers citing "Is PGD-Adversarial Training Necessary? Alternative Training via a Soft-Quantization Network with Noisy-Natural Samples Only"

17 / 17 papers shown

Title
Distributionally Adversarial Attack T. Zheng Changyou Chen K. Ren OOD 95 121 0 16 Aug 2018
Defend Deep Neural Networks Against Adversarial Examples via Fixed and Dynamic Quantized Activation Functions Adnan Siraj Rakin Jinfeng Yi Boqing Gong Deliang Fan AAML MQ 69 50 0 18 Jul 2018
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models Pouya Samangouei Maya Kabkab Rama Chellappa AAML GAN 86 1,179 0 17 May 2018
Curriculum Adversarial Training Qi-Zhi Cai Min Du Chang-rui Liu Basel Alomair AAML 80 165 0 13 May 2018
Adversarial Logit Pairing Harini Kannan Alexey Kurakin Ian Goodfellow AAML 98 629 0 16 Mar 2018
Stochastic Activation Pruning for Robust Adversarial Defense Guneet Singh Dhillon Kamyar Azizzadenesheli Zachary Chase Lipton Jeremy Bernstein Jean Kossaifi Aran Khanna Anima Anandkumar AAML 84 547 0 05 Mar 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 249 3,194 0 01 Feb 2018
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality Xingjun Ma Yue Liu Yisen Wang S. Erfani S. Wijewickrema Grant Schoenebeck Basel Alomair Michael E. Houle James Bailey AAML 116 742 0 08 Jan 2018
Mitigating Adversarial Effects Through Randomization Cihang Xie Jianyu Wang Zhishuai Zhang Zhou Ren Alan Yuille AAML 122 1,062 0 06 Nov 2017
Countering Adversarial Images using Input Transformations Chuan Guo Mayank Rana Moustapha Cissé Laurens van der Maaten AAML 135 1,406 0 31 Oct 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 163 2,160 0 21 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 319 12,151 0 19 Jun 2017
Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong Warren He James Wei Xinyun Chen Nicholas Carlini Basel Alomair AAML 102 242 0 15 Jun 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 177 2,729 0 19 May 2017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks Weilin Xu David Evans Yanjun Qi AAML 97 1,273 0 04 Apr 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 477 3,148 0 04 Nov 2016
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 85 3,685 0 08 Feb 2016