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Scaling provable adversarial defenses

31 May 2018

J. Zico Kolter

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Papers citing "Scaling provable adversarial defenses"

50 / 273 papers shown

Title
Debona: Decoupled Boundary Network Analysis for Tighter Bounds and Faster Adversarial Robustness Proofs Christopher Brix T. Noll AAML 64 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 134 82 0 15 Jun 2020
On the Tightness of Semidefinite Relaxations for Certifying Robustness to Adversarial Examples Richard Y. Zhang AAML 55 26 0 11 Jun 2020
Towards Understanding Fast Adversarial Training Bai Li Shiqi Wang Suman Jana Lawrence Carin AAML 78 50 0 04 Jun 2020
Second-Order Provable Defenses against Adversarial Attacks Sahil Singla Soheil Feizi AAML 74 60 0 01 Jun 2020
Exploring Model Robustness with Adaptive Networks and Improved Adversarial Training Zheng Xu Ali Shafahi Tom Goldstein AAML 51 2 0 30 May 2020
Enhancing Certified Robustness via Smoothed Weighted Ensembling Chizhou Liu Yunzhen Feng Ranran Wang Bin Dong AAML 80 12 0 19 May 2020
Encryption Inspired Adversarial Defense for Visual Classification Maungmaung Aprilpyone Hitoshi Kiya 56 32 0 16 May 2020
Online Monitoring for Neural Network Based Monocular Pedestrian Pose Estimation Arjun Gupta Luca Carlone 3DH 38 9 0 11 May 2020
Provable Robust Classification via Learned Smoothed Densities Saeed Saremi R. Srivastava AAML 74 3 0 09 May 2020
Robustness Certification of Generative Models M. Mirman Timon Gehr Martin Vechev AAML 70 21 0 30 Apr 2020
Provably robust deep generative models Filipe Condessa Zico Kolter AAML OOD 31 5 0 22 Apr 2020
Safety-Aware Hardening of 3D Object Detection Neural Network Systems Chih-Hong Cheng 3DPC 55 12 0 25 Mar 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability Maximilian Augustin Alexander Meinke Matthias Hein OOD 191 102 0 20 Mar 2020
Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations Huan Zhang Hongge Chen Chaowei Xiao Yue Liu Mingyan D. Liu Duane S. Boning Cho-Jui Hsieh AAML 176 275 0 19 Mar 2020
Breaking certified defenses: Semantic adversarial examples with spoofed robustness certificates Amin Ghiasi Ali Shafahi Tom Goldstein 102 55 0 19 Mar 2020
Vulnerabilities of Connectionist AI Applications: Evaluation and Defence Christian Berghoff Matthias Neu Arndt von Twickel AAML 109 25 0 18 Mar 2020
Verification of Neural Networks: Enhancing Scalability through Pruning Dario Guidotti Francesco Leofante Luca Pulina A. Tacchella 39 24 0 17 Mar 2020
Denoised Smoothing: A Provable Defense for Pretrained Classifiers Hadi Salman Mingjie Sun Greg Yang Ashish Kapoor J. Zico Kolter 94 23 0 04 Mar 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks Francesco Croce Matthias Hein AAML 275 1,864 0 03 Mar 2020
Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative Models Xiao Zhang Jinghui Chen Quanquan Gu David Evans 76 17 0 01 Mar 2020
Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond Kaidi Xu Zhouxing Shi Huan Zhang Yihan Wang Kai-Wei Chang Minlie Huang B. Kailkhura Xinyu Lin Cho-Jui Hsieh AAML 61 12 0 28 Feb 2020
TSS: Transformation-Specific Smoothing for Robustness Certification Linyi Li Maurice Weber Xiaojun Xu Luka Rimanic B. Kailkhura Tao Xie Ce Zhang Yue Liu AAML 145 57 0 27 Feb 2020
Improving Robustness of Deep-Learning-Based Image Reconstruction Ankit Raj Y. Bresler Yue Liu OOD AAML 96 51 0 26 Feb 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 159 811 0 26 Feb 2020
Towards Backdoor Attacks and Defense in Robust Machine Learning Models E. Soremekun Sakshi Udeshi Sudipta Chattopadhyay AAML 24 14 0 25 Feb 2020
Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers Chen Zhu Renkun Ni Ping Yeh-Chiang Hengduo Li Furong Huang Tom Goldstein 87 5 0 22 Feb 2020
Towards Certifiable Adversarial Sample Detection Ilia Shumailov Yiren Zhao Robert D. Mullins Ross J. Anderson AAML 51 13 0 20 Feb 2020
Randomized Smoothing of All Shapes and Sizes Greg Yang Tony Duan J. E. Hu Hadi Salman Ilya P. Razenshteyn Jungshian Li AAML 97 216 0 19 Feb 2020
The Conditional Entropy Bottleneck Ian S. Fischer OOD 117 122 0 13 Feb 2020
Improving the affordability of robustness training for DNNs Sidharth Gupta Parijat Dube Ashish Verma AAML 57 15 0 11 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 78 79 0 10 Feb 2020
Weighted Average Precision: Adversarial Example Detection in the Visual Perception of Autonomous Vehicles Yilan Li Senem Velipasalar AAML 22 7 0 25 Jan 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 106 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 86 64 0 16 Jan 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 150 1,182 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 111 178 0 08 Jan 2020
PaRoT: A Practical Framework for Robust Deep Neural Network Training Edward W. Ayers Francisco Eiras Majd Hawasly I. Whiteside OOD 97 19 0 07 Jan 2020
Benchmarking Adversarial Robustness Yinpeng Dong Qi-An Fu Xiao Yang Tianyu Pang Hang Su Zihao Xiao Jun Zhu AAML 108 36 0 26 Dec 2019
Jacobian Adversarially Regularized Networks for Robustness Alvin Chan Yi Tay Yew-Soon Ong Jie Fu AAML 92 76 0 21 Dec 2019
Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing Jinyuan Jia Xiaoyu Cao Binghui Wang Neil Zhenqiang Gong AAML 60 96 0 20 Dec 2019
Towards Verifying Robustness of Neural Networks Against Semantic Perturbations Jeet Mohapatra Tsui-Wei Weng Weng Pin-Yu Chen Sijia Liu Luca Daniel AAML 69 18 0 19 Dec 2019
What it Thinks is Important is Important: Robustness Transfers through Input Gradients Alvin Chan Yi Tay Yew-Soon Ong AAML OOD 79 52 0 11 Dec 2019
Training Provably Robust Models by Polyhedral Envelope Regularization Chen Liu Mathieu Salzmann Sabine Süsstrunk AAML 78 8 0 10 Dec 2019
Cost-Aware Robust Tree Ensembles for Security Applications Yizheng Chen Shiqi Wang Weifan Jiang Asaf Cidon Suman Jana AAML OOD 39 5 0 03 Dec 2019
A Method for Computing Class-wise Universal Adversarial Perturbations Tejus Gupta Abhishek Sinha Nupur Kumari M. Singh Balaji Krishnamurthy AAML 38 10 0 01 Dec 2019
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks Qiyang Li Saminul Haque Cem Anil James Lucas Roger C. Grosse Joern-Henrik Jacobsen 124 116 0 03 Nov 2019
Online Robustness Training for Deep Reinforcement Learning Marc Fischer M. Mirman Steven Stalder Martin Vechev OnRL 102 41 0 03 Nov 2019
MadNet: Using a MAD Optimization for Defending Against Adversarial Attacks Shai Rozenberg G. Elidan Ran El-Yaniv AAML 30 1 0 03 Nov 2019
Enhancing Certifiable Robustness via a Deep Model Ensemble Huan Zhang Minhao Cheng Cho-Jui Hsieh 72 9 0 31 Oct 2019