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Provable defenses against adversarial examples via the convex outer adversarial polytope

2 November 2017

Eric Wong

J. Zico Kolter

AAML

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Papers citing "Provable defenses against adversarial examples via the convex outer adversarial polytope"

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Title
Adversarial Training for Free! Ali Shafahi Mahyar Najibi Amin Ghiasi Zheng Xu John P. Dickerson Christoph Studer L. Davis Gavin Taylor Tom Goldstein AAML 139 1,254 0 29 Apr 2019
Distributed generation of privacy preserving data with user customization Xiao Chen Thomas Navidi Stefano Ermon Ram Rajagopal 69 11 0 20 Apr 2019
Reward Potentials for Planning with Learned Neural Network Transition Models B. Say Scott Sanner Sylvie Thiébaux 32 4 0 19 Apr 2019
Gotta Catch Ém All: Using Honeypots to Catch Adversarial Attacks on Neural Networks Shawn Shan Emily Wenger Bolun Wang Yangqiu Song Haitao Zheng Ben Y. Zhao 89 75 0 18 Apr 2019
Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks David J. Miller Zhen Xiang G. Kesidis AAML 74 35 0 12 Apr 2019
The coupling effect of Lipschitz regularization in deep neural networks Nicolas P. Couellan 40 5 0 12 Apr 2019
Universal Lipschitz Approximation in Bounded Depth Neural Networks Jérémy E. Cohen Todd P. Huster Ravid Cohen AAML 65 23 0 09 Apr 2019
On Training Robust PDF Malware Classifiers Yizheng Chen Shiqi Wang Dongdong She Suman Jana AAML 99 69 0 06 Apr 2019
Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks Yinpeng Dong Tianyu Pang Hang Su Jun Zhu SILM AAML 96 856 0 05 Apr 2019
Minimum Uncertainty Based Detection of Adversaries in Deep Neural Networks Fatemeh Sheikholeslami Swayambhoo Jain G. Giannakis AAML 67 25 0 05 Apr 2019
Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks Aamir Mustafa Salman Khan Munawar Hayat Roland Göcke Jianbing Shen Ling Shao AAML 64 152 0 01 Apr 2019
A Provable Defense for Deep Residual Networks M. Mirman Gagandeep Singh Martin Vechev 82 26 0 29 Mar 2019
Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks Francesco Croce Jonas Rauber Matthias Hein AAML 60 31 0 27 Mar 2019
Defending against Whitebox Adversarial Attacks via Randomized Discretization Yuchen Zhang Percy Liang AAML 79 76 0 25 Mar 2019
Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness J. Jacobsen Jens Behrmann Nicholas Carlini Florian Tramèr Nicolas Papernot AAML 79 46 0 25 Mar 2019
The LogBarrier adversarial attack: making effective use of decision boundary information Chris Finlay Aram-Alexandre Pooladian Adam M. Oberman AAML 79 25 0 25 Mar 2019
A Formalization of Robustness for Deep Neural Networks T. Dreossi Shromona Ghosh Alberto L. Sangiovanni-Vincentelli Sanjit A. Seshia GAN 71 30 0 24 Mar 2019
Scalable Differential Privacy with Certified Robustness in Adversarial Learning Nhathai Phan My T. Thai Han Hu R. Jin Tong Sun Dejing Dou 91 14 0 23 Mar 2019
Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes Matt Jordan Justin Lewis A. Dimakis AAML 79 57 0 20 Mar 2019
Algorithms for Verifying Deep Neural Networks Changliu Liu Tomer Arnon Christopher Lazarus Christopher A. Strong Clark W. Barrett Mykel J. Kochenderfer AAML 102 403 0 15 Mar 2019
On Evaluation of Adversarial Perturbations for Sequence-to-Sequence Models Paul Michel Xian Li Graham Neubig J. Pino AAML 79 136 0 15 Mar 2019
On Certifying Non-uniform Bound against Adversarial Attacks Chen Liu Ryota Tomioka Volkan Cevher AAML 79 19 0 15 Mar 2019
A Research Agenda: Dynamic Models to Defend Against Correlated Attacks Ian Goodfellow AAML OOD 85 31 0 14 Mar 2019
Semantics Preserving Adversarial Learning Ousmane Amadou Dia Elnaz Barshan Reza Babanezhad AAML GAN 100 2 0 10 Mar 2019
Detecting Overfitting via Adversarial Examples Roman Werpachowski András Gyorgy Csaba Szepesvári TDI 86 45 0 06 Mar 2019
Safety Verification and Robustness Analysis of Neural Networks via Quadratic Constraints and Semidefinite Programming Mahyar Fazlyab M. Morari George J. Pappas AAML 92 233 0 04 Mar 2019
A Fundamental Performance Limitation for Adversarial Classification Abed AlRahman Al Makdah Vaibhav Katewa Fabio Pasqualetti AAML 50 9 0 04 Mar 2019
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations Saeid Asgari Taghanaki Kumar Abhishek Shekoofeh Azizi Ghassan Hamarneh AAML 89 41 0 03 Mar 2019
Robust Decision Trees Against Adversarial Examples Hongge Chen Huan Zhang Duane S. Boning Cho-Jui Hsieh AAML 140 117 0 27 Feb 2019
Architecting Dependable Learning-enabled Autonomous Systems: A Survey Chih-Hong Cheng Dhiraj Gulati Rongjie Yan 44 4 0 27 Feb 2019
Disentangled Deep Autoencoding Regularization for Robust Image Classification Zhenyu Duan Martin Renqiang Min Erran L. Li Mingbo Cai Yi Tian Xu Bingbing Ni 24 2 0 27 Feb 2019
Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification Jianlin Li Pengfei Yang Jiangchao Liu Liqian Chen Xiaowei Huang Lijun Zhang AAML 76 80 0 26 Feb 2019
Verification of Non-Linear Specifications for Neural Networks Chongli Qin Krishnamurthy Dvijotham Dvijotham Brendan O'Donoghue Rudy Bunel Robert Stanforth Sven Gowal J. Uesato G. Swirszcz Pushmeet Kohli AAML 68 44 0 25 Feb 2019
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks Hadi Salman Greg Yang Huan Zhang Cho-Jui Hsieh Pengchuan Zhang AAML 144 271 0 23 Feb 2019
On the Sensitivity of Adversarial Robustness to Input Data Distributions G. Ding Kry Yik-Chau Lui Xiaomeng Jin Luyu Wang Ruitong Huang OOD 64 60 0 22 Feb 2019
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations Eric Wong Frank R. Schmidt J. Zico Kolter AAML 95 211 0 21 Feb 2019
advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch G. Ding Luyu Wang Xiaomeng Jin 72 183 0 20 Feb 2019
Fast Neural Network Verification via Shadow Prices Vicencc Rubies-Royo Roberto Calandra D. Stipanović Claire Tomlin AAML 89 41 0 19 Feb 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 141 905 0 18 Feb 2019
VC Classes are Adversarially Robustly Learnable, but Only Improperly Omar Montasser Steve Hanneke Nathan Srebro 85 141 0 12 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 207 2,056 0 08 Feb 2019
Robustness Certificates Against Adversarial Examples for ReLU Networks Sahil Singla Soheil Feizi AAML 68 21 0 01 Feb 2019
A New Family of Neural Networks Provably Resistant to Adversarial Attacks Rakshit Agrawal Luca de Alfaro D. Helmbold AAML OOD 39 2 0 01 Feb 2019
Augmenting Model Robustness with Transformation-Invariant Attacks Houpu Yao Zhe Wang Guangyu Nie Yassine Mazboudi Yezhou Yang Yi Ren AAML OOD 31 3 0 31 Jan 2019
A Simple Explanation for the Existence of Adversarial Examples with Small Hamming Distance A. Shamir Itay Safran Eyal Ronen O. Dunkelman GAN AAML 59 95 0 30 Jan 2019
Defense Methods Against Adversarial Examples for Recurrent Neural Networks Ishai Rosenberg A. Shabtai Yuval Elovici Lior Rokach AAML GAN 81 42 0 28 Jan 2019
Characterizing the Shape of Activation Space in Deep Neural Networks Thomas Gebhart Paul Schrater Alan Hylton AAML 52 7 0 28 Jan 2019
On the (In)fidelity and Sensitivity for Explanations Chih-Kuan Yeh Cheng-Yu Hsieh A. Suggala David I. Inouye Pradeep Ravikumar FAtt 110 456 0 27 Jan 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 175 2,566 0 24 Jan 2019
The Limitations of Adversarial Training and the Blind-Spot Attack Huan Zhang Hongge Chen Zhao Song Duane S. Boning Inderjit S. Dhillon Cho-Jui Hsieh AAML 73 145 0 15 Jan 2019