Certified Adversarial Robustness via Randomized Smoothing

8 February 2019

J. Zico Kolter

Papers citing "Certified Adversarial Robustness via Randomized Smoothing"

37 / 537 papers shown

Title
Fine-grained Synthesis of Unrestricted Adversarial Examples Omid Poursaeed Tianxing Jiang Yordanos Goshu Harry Yang Serge J. Belongie Ser-Nam Lim AAML 42 13 0 20 Nov 2019
Where is the Bottleneck of Adversarial Learning with Unlabeled Data? Jingfeng Zhang Bo Han Gang Niu Tongliang Liu Masashi Sugiyama 30 6 0 20 Nov 2019
Towards Large yet Imperceptible Adversarial Image Perturbations with Perceptual Color Distance Zhengyu Zhao Zhuoran Liu Martha Larson AAML 23 143 0 06 Nov 2019
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks Qiyang Li Saminul Haque Cem Anil James Lucas Roger C. Grosse Joern-Henrik Jacobsen 28 114 0 03 Nov 2019
Adversarial Examples for Cost-Sensitive Classifiers Mahdi Akbari Zarkesh A. Lohn Ali Movaghar SILM AAML 24 3 0 04 Oct 2019
Partial differential equation regularization for supervised machine learning Jillian R. Fisher 35 2 0 03 Oct 2019
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts Yu Sun Xiaolong Wang Zhuang Liu John Miller Alexei A. Efros Moritz Hardt TTA OOD 27 92 0 29 Sep 2019
Towards neural networks that provably know when they don't know Alexander Meinke Matthias Hein OODD 33 139 0 26 Sep 2019
Defending Against Physically Realizable Attacks on Image Classification Tong Wu Liang Tong Yevgeniy Vorobeychik AAML 25 126 0 20 Sep 2019
Implicit Deep Learning L. Ghaoui Fangda Gu Bertrand Travacca Armin Askari Alicia Y. Tsai AI4CE 39 176 0 17 Aug 2019
Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks Jiadong Lin Chuanbiao Song Kun He Liwei Wang John E. Hopcroft AAML 41 555 0 17 Aug 2019
BlurNet: Defense by Filtering the Feature Maps Ravi Raju Mikko H. Lipasti AAML 42 15 0 06 Aug 2019
A unified view on differential privacy and robustness to adversarial examples Rafael Pinot Florian Yger Cédric Gouy-Pailler Jamal Atif AAML 21 17 0 19 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 26 345 0 14 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 45 541 0 09 Jun 2019
Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang Tianyun Zhang Sijia Liu Pin-Yu Chen Jiacen Xu M. Fardad Yangqiu Song AAML 32 35 0 09 Jun 2019
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks Maksym Andriushchenko Matthias Hein 35 61 0 08 Jun 2019
Certifiably Robust Interpretation in Deep Learning Alexander Levine Sahil Singla Soheil Feizi FAtt AAML 33 63 0 28 May 2019
Scaleable input gradient regularization for adversarial robustness Chris Finlay Adam M. Oberman AAML 21 78 0 27 May 2019
Robust Classification using Robust Feature Augmentation Kevin Eykholt Swati Gupta Atul Prakash Amir Rahmati Pratik Vaishnavi Haizhong Zheng AAML 24 2 0 26 May 2019
Enhancing Adversarial Defense by k-Winners-Take-All Chang Xiao Peilin Zhong Changxi Zheng AAML 27 97 0 25 May 2019
Privacy Risks of Securing Machine Learning Models against Adversarial Examples Liwei Song Reza Shokri Prateek Mittal SILM MIACV AAML 6 236 0 24 May 2019
Percival: Making In-Browser Perceptual Ad Blocking Practical With Deep Learning Z. Din P. Tigas Samuel T. King B. Livshits VLM 39 29 0 17 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 79 1,234 0 29 Apr 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
Statistical Guarantees for the Robustness of Bayesian Neural Networks L. Cardelli Marta Kwiatkowska Luca Laurenti Nicola Paoletti A. Patané Matthew Wicker AAML 31 54 0 05 Mar 2019
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks Hadi Salman Greg Yang Huan Zhang Cho-Jui Hsieh Pengchuan Zhang AAML 52 264 0 23 Feb 2019
On the (In)fidelity and Sensitivity for Explanations Chih-Kuan Yeh Cheng-Yu Hsieh A. Suggala David I. Inouye Pradeep Ravikumar FAtt 41 449 0 27 Jan 2019
On the Security of Randomized Defenses Against Adversarial Samples K. Sharad G. Marson H. Truong Ghassan O. Karame AAML 35 1 0 11 Dec 2018
MMA Training: Direct Input Space Margin Maximization through Adversarial Training G. Ding Yash Sharma Kry Yik-Chau Lui Ruitong Huang AAML 27 270 0 06 Dec 2018
Certified Adversarial Robustness with Additive Noise Bai Li Changyou Chen Wenlin Wang Lawrence Carin AAML 28 342 0 10 Sep 2018
Adversarial examples from computational constraints Sébastien Bubeck Eric Price Ilya P. Razenshteyn AAML 67 230 0 25 May 2018
Robust GANs against Dishonest Adversaries Zhi Xu Chengtao Li Stefanie Jegelka AAML 36 3 0 27 Feb 2018
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 97 2,706 0 19 May 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 251 1,843 0 03 Feb 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 323 3,117 0 04 Nov 2016
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 183 932 0 21 Oct 2016