Scaling provable adversarial defenses

31 May 2018

J. Zico Kolter

Papers citing "Scaling provable adversarial defenses"

50 / 115 papers shown

Title
Block-wise Image Transformation with Secret Key for Adversarially Robust Defense Maungmaung Aprilpyone Hitoshi Kiya 29 57 0 02 Oct 2020
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Bo-wen Li AAML 35 128 0 09 Sep 2020
Robust Machine Learning via Privacy/Rate-Distortion Theory Ye Wang Shuchin Aeron Adnan Siraj Rakin T. Koike-Akino P. Moulin OOD 22 6 0 22 Jul 2020
The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network Verification Christian Tjandraatmadja Ross Anderson Joey Huchette Will Ma Krunal Patel J. Vielma AAML 27 89 0 24 Jun 2020
Defense against Adversarial Attacks in NLP via Dirichlet Neighborhood Ensemble Yi Zhou Xiaoqing Zheng Cho-Jui Hsieh Kai-Wei Chang Xuanjing Huang SILM 39 48 0 20 Jun 2020
From Discrete to Continuous Convolution Layers Assaf Shocher Ben Feinstein Niv Haim Michal Irani 10 17 0 19 Jun 2020
Debona: Decoupled Boundary Network Analysis for Tighter Bounds and Faster Adversarial Robustness Proofs Christopher Brix T. Noll AAML 25 10 0 16 Jun 2020
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them Chen Liu Mathieu Salzmann Tao R. Lin Ryota Tomioka Sabine Süsstrunk AAML 24 81 0 15 Jun 2020
Encryption Inspired Adversarial Defense for Visual Classification Maungmaung Aprilpyone Hitoshi Kiya 24 32 0 16 May 2020
Robustness Certification of Generative Models M. Mirman Timon Gehr Martin Vechev AAML 43 22 0 30 Apr 2020
Provably robust deep generative models Filipe Condessa Zico Kolter AAML OOD 14 5 0 22 Apr 2020
Safety-Aware Hardening of 3D Object Detection Neural Network Systems Chih-Hong Cheng 3DPC 27 12 0 25 Mar 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability Maximilian Augustin Alexander Meinke Matthias Hein OOD 75 99 0 20 Mar 2020
Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations Huan Zhang Hongge Chen Chaowei Xiao Bo-wen Li Mingyan D. Liu Duane S. Boning Cho-Jui Hsieh AAML 47 261 0 19 Mar 2020
Breaking certified defenses: Semantic adversarial examples with spoofed robustness certificates Amin Ghiasi Ali Shafahi Tom Goldstein 33 55 0 19 Mar 2020
Improving Robustness of Deep-Learning-Based Image Reconstruction Ankit Raj Y. Bresler Bo-wen Li OOD AAML 29 50 0 26 Feb 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 47 788 0 26 Feb 2020
The Conditional Entropy Bottleneck Ian S. Fischer OOD 29 116 0 13 Feb 2020
$Random Smoothing Might be Unable to Certify $\ell_\infty$ Robustness for High-Dimensional Images$ Random Smoothing Might be Unable to Certify $\ell_\infty$ Robustness for High-Dimensional Images Avrim Blum Travis Dick N. Manoj Hongyang R. Zhang AAML 31 79 0 10 Feb 2020
Safety Concerns and Mitigation Approaches Regarding the Use of Deep Learning in Safety-Critical Perception Tasks Oliver Willers Sebastian Sudholt Shervin Raafatnia Stephanie Abrecht 28 80 0 22 Jan 2020
A simple way to make neural networks robust against diverse image corruptions E. Rusak Lukas Schott Roland S. Zimmermann Julian Bitterwolf Oliver Bringmann Matthias Bethge Wieland Brendel 21 64 0 16 Jan 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 99 1,160 0 12 Jan 2020
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius Runtian Zhai Chen Dan Di He Huan Zhang Boqing Gong Pradeep Ravikumar Cho-Jui Hsieh Liwei Wang OOD AAML 27 177 0 08 Jan 2020
Benchmarking Adversarial Robustness Yinpeng Dong Qi-An Fu Xiao Yang Tianyu Pang Hang Su Zihao Xiao Jun Zhu AAML 31 36 0 26 Dec 2019
Enhancing Certifiable Robustness via a Deep Model Ensemble Huan Zhang Minhao Cheng Cho-Jui Hsieh 33 9 0 31 Oct 2019
Defending Against Physically Realizable Attacks on Image Classification Tong Wu Liang Tong Yevgeniy Vorobeychik AAML 25 125 0 20 Sep 2019
ART: Abstraction Refinement-Guided Training for Provably Correct Neural Networks Xuankang Lin He Zhu R. Samanta Suresh Jagannathan AAML 27 28 0 17 Jul 2019
Towards Stable and Efficient Training of Verifiably Robust Neural Networks Huan Zhang Hongge Chen Chaowei Xiao Sven Gowal Robert Stanforth Bo-wen Li Duane S. Boning Cho-Jui Hsieh AAML 17 344 0 14 Jun 2019
Evaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective Lu Wang Xuanqing Liu Jinfeng Yi Zhi-Hua Zhou Cho-Jui Hsieh AAML 28 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 22 76 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 45 538 0 09 Jun 2019
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks Maksym Andriushchenko Matthias Hein 28 61 0 08 Jun 2019
Enhancing Gradient-based Attacks with Symbolic Intervals Shiqi Wang Yizheng Chen Ahmed Abdou Suman Jana AAML 31 15 0 05 Jun 2019
Controlling Neural Level Sets Matan Atzmon Niv Haim Lior Yariv Ofer Israelov Haggai Maron Y. Lipman AI4CE 22 118 0 28 May 2019
Adversarially Robust Learning Could Leverage Computational Hardness Sanjam Garg S. Jha Saeed Mahloujifar Mohammad Mahmoody AAML 23 24 0 28 May 2019
Scaleable input gradient regularization for adversarial robustness Chris Finlay Adam M. Oberman AAML 16 77 0 27 May 2019
Privacy Risks of Securing Machine Learning Models against Adversarial Examples Liwei Song Reza Shokri Prateek Mittal SILM MIACV AAML 6 235 0 24 May 2019
Testing DNN Image Classifiers for Confusion & Bias Errors Yuchi Tian Ziyuan Zhong Vicente Ordonez Gail E. Kaiser Baishakhi Ray 24 52 0 20 May 2019
What Do Adversarially Robust Models Look At? Takahiro Itazuri Yoshihiro Fukuhara Hirokatsu Kataoka Shigeo Morishima 19 5 0 19 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 68 1,231 0 29 Apr 2019
On Training Robust PDF Malware Classifiers Yizheng Chen Shiqi Wang Dongdong She Suman Jana AAML 50 68 0 06 Apr 2019
Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks Francesco Croce Jonas Rauber Matthias Hein AAML 20 30 0 27 Mar 2019
Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness J. Jacobsen Jens Behrmann Nicholas Carlini Florian Tramèr Nicolas Papernot AAML 24 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 27 57 0 20 Mar 2019
On Certifying Non-uniform Bound against Adversarial Attacks Chen Liu Ryota Tomioka V. Cevher AAML 42 19 0 15 Mar 2019
Robust Decision Trees Against Adversarial Examples Hongge Chen Huan Zhang Duane S. Boning Cho-Jui Hsieh AAML 31 116 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 16 43 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 35 263 0 23 Feb 2019
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations Eric Wong Frank R. Schmidt J. Zico Kolter AAML 36 210 0 21 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 22 1,998 0 08 Feb 2019