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Scaling provable adversarial defenses

31 May 2018

J. Zico Kolter

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Papers citing "Scaling provable adversarial defenses"

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Title
A Fast Saddle-Point Dynamical System Approach to Robust Deep Learning Yasaman Esfandiari Aditya Balu K. Ebrahimi Umesh Vaidya N. Elia Soumik Sarkar OOD 47 3 0 18 Oct 2019
Universal Approximation with Certified Networks Maximilian Baader M. Mirman Martin Vechev 71 22 0 30 Sep 2019
Towards Robust Direct Perception Networks for Automated Driving Chih-Hong Cheng 16 1 0 30 Sep 2019
Defending Against Physically Realizable Attacks on Image Classification Tong Wu Liang Tong Yevgeniy Vorobeychik AAML 84 126 0 20 Sep 2019
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review Han Xu Yao Ma Haochen Liu Debayan Deb Hui Liu Jiliang Tang Anil K. Jain AAML 79 680 0 17 Sep 2019
Adversarial Robustness Against the Union of Multiple Perturbation Models Pratyush Maini Eric Wong J. Zico Kolter OOD AAML 63 151 0 09 Sep 2019
Understanding Adversarial Robustness: The Trade-off between Minimum and Average Margin Kaiwen Wu Yaoliang Yu AAML 45 8 0 26 Jul 2019
Connecting Lyapunov Control Theory to Adversarial Attacks Arash Rahnama A. Nguyen Edward Raff AAML 21 6 0 17 Jul 2019
ART: Abstraction Refinement-Guided Training for Provably Correct Neural Networks Xuankang Lin He Zhu R. Samanta Suresh Jagannathan AAML 92 29 0 17 Jul 2019
Towards Robust, Locally Linear Deep Networks Guang-He Lee David Alvarez-Melis Tommi Jaakkola ODL 135 48 0 07 Jul 2019
Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Too Much Accuracy Alex Lamb Vikas Verma Kenji Kawaguchi Alexander Matyasko Savya Khosla Arno Solin Yoshua Bengio AAML 70 99 0 16 Jun 2019
Towards Stable and Efficient Training of Verifiably Robust Neural Networks Huan Zhang Hongge Chen Chaowei Xiao Sven Gowal Robert Stanforth Yue Liu Duane S. Boning Cho-Jui Hsieh AAML 107 351 0 14 Jun 2019
Towards Compact and Robust Deep Neural Networks Vikash Sehwag Shiqi Wang Prateek Mittal Suman Jana AAML 82 40 0 14 Jun 2019
Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers Guang-He Lee Yang Yuan Shiyu Chang Tommi Jaakkola AAML 73 127 0 12 Jun 2019
Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks Mahyar Fazlyab Alexander Robey Hamed Hassani M. Morari George J. Pappas 142 462 0 12 Jun 2019
Evaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective Lu Wang Xuanqing Liu Jinfeng Yi Zhi Zhou Cho-Jui Hsieh AAML 83 22 0 10 Jun 2019
Robustness Verification of Tree-based Models Hongge Chen Huan Zhang Si Si Yang Li Duane S. Boning Cho-Jui Hsieh AAML 103 77 0 10 Jun 2019
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 131 552 0 09 Jun 2019
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks Maksym Andriushchenko Matthias Hein 84 62 0 08 Jun 2019
Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robustness Walt Woods Jack H Chen C. Teuscher AAML 66 46 0 07 Jun 2019
Enhancing Gradient-based Attacks with Symbolic Intervals Shiqi Wang Yizheng Chen Ahmed Abdou Suman Jana AAML 58 15 0 05 Jun 2019
Correctness Verification of Neural Networks Yichen Yang Martin Rinard AAML 67 12 0 03 Jun 2019
Unlabeled Data Improves Adversarial Robustness Y. Carmon Aditi Raghunathan Ludwig Schmidt Percy Liang John C. Duchi 130 754 0 31 May 2019
Are Labels Required for Improving Adversarial Robustness? J. Uesato Jean-Baptiste Alayrac Po-Sen Huang Robert Stanforth Alhussein Fawzi Pushmeet Kohli AAML 95 335 0 31 May 2019
Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness Saeed Mahloujifar Xiao Zhang Mohammad Mahmoody David Evans 64 22 0 29 May 2019
Controlling Neural Level Sets Matan Atzmon Niv Haim Lior Yariv Ofer Israelov Haggai Maron Y. Lipman AI4CE 54 121 0 28 May 2019
Adversarially Robust Learning Could Leverage Computational Hardness Sanjam Garg S. Jha Saeed Mahloujifar Mohammad Mahmoody AAML 163 24 0 28 May 2019
Scaleable input gradient regularization for adversarial robustness Chris Finlay Adam M. Oberman AAML 101 79 0 27 May 2019
$Provable robustness against all adversarial $l_p$-perturbations for $p\geq 1$$ Provable robustness against all adversarial $l_p$ -perturbations for $p\geq 1$ Francesco Croce Matthias Hein OOD 78 75 0 27 May 2019
Privacy Risks of Securing Machine Learning Models against Adversarial Examples Liwei Song Reza Shokri Prateek Mittal SILM MIACV AAML 88 248 0 24 May 2019
Testing DNN Image Classifiers for Confusion & Bias Errors Yuchi Tian Ziyuan Zhong Vicente Ordonez Gail E. Kaiser Baishakhi Ray 153 53 0 20 May 2019
What Do Adversarially Robust Models Look At? Takahiro Itazuri Yoshihiro Fukuhara Hirokatsu Kataoka Shigeo Morishima 32 5 0 19 May 2019
Better the Devil you Know: An Analysis of Evasion Attacks using Out-of-Distribution Adversarial Examples Vikash Sehwag A. Bhagoji Liwei Song Chawin Sitawarin Daniel Cullina M. Chiang Prateek Mittal OODD 77 26 0 05 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 139 1,254 0 29 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
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
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
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
On Certifying Non-uniform Bound against Adversarial Attacks Chen Liu Ryota Tomioka Volkan Cevher AAML 79 19 0 15 Mar 2019
Robust Decision Trees Against Adversarial Examples Hongge Chen Huan Zhang Duane S. Boning Cho-Jui Hsieh AAML 142 117 0 27 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 146 271 0 23 Feb 2019
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations Eric Wong Frank R. Schmidt J. Zico Kolter AAML 95 211 0 21 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 210 2,056 0 08 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
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 187 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
Adversarial Attacks, Regression, and Numerical Stability Regularization A. Nguyen Edward Raff AAML 44 30 0 07 Dec 2018