v1v2 (latest)

Certified Adversarial Robustness via Randomized Smoothing

8 February 2019

Jeremy M. Cohen

Elan Rosenfeld

J. Zico Kolter

AAML

ArXiv (abs)PDF HTML Github (390★)

Papers citing "Certified Adversarial Robustness via Randomized Smoothing"

50 / 1,313 papers shown

Title
Structure Matters: Towards Generating Transferable Adversarial Images Dan Peng Zizhan Zheng Linhao Luo Xiaofeng Zhang AAML 95 2 0 22 Oct 2019
Are Perceptually-Aligned Gradients a General Property of Robust Classifiers? Simran Kaur Jeremy M. Cohen Zachary Chase Lipton OOD AAML 78 66 0 18 Oct 2019
Extracting robust and accurate features via a robust information bottleneck Ankit Pensia Varun Jog Po-Ling Loh AAML 78 21 0 15 Oct 2019
Noise as a Resource for Learning in Knowledge Distillation Elahe Arani F. Sarfraz Bahram Zonooz 64 6 0 11 Oct 2019
Yet another but more efficient black-box adversarial attack: tiling and evolution strategies Laurent Meunier Cen Chen Li Wang MLAU AAML 140 40 0 05 Oct 2019
Adversarial Examples for Cost-Sensitive Classifiers Mahdi Akbari Zarkesh A. Lohn Ali Movaghar SILM AAML 60 3 0 04 Oct 2019
Partial differential equation regularization for supervised machine learning Jillian R. Fisher 76 2 0 03 Oct 2019
Analyzing and Improving Neural Networks by Generating Semantic Counterexamples through Differentiable Rendering Lakshya Jain Varun Chandrasekaran Uyeong Jang Wilson Wu Andrew Lee Andy Yan Steven Chen S. Jha Sanjit A. Seshia AAML 72 11 0 02 Oct 2019
Truth or Backpropaganda? An Empirical Investigation of Deep Learning Theory Micah Goldblum Jonas Geiping Avi Schwarzschild Michael Moeller Tom Goldstein 138 34 0 01 Oct 2019
Universal Approximation with Certified Networks Maximilian Baader M. Mirman Martin Vechev 74 22 0 30 Sep 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 112 96 0 29 Sep 2019
Towards neural networks that provably know when they don't know Alexander Meinke Matthias Hein OODD 108 141 0 26 Sep 2019
FENCE: Feasible Evasion Attacks on Neural Networks in Constrained Environments Alesia Chernikova Alina Oprea AAML 121 40 0 23 Sep 2019
Defending Against Physically Realizable Attacks on Image Classification Tong Wu Liang Tong Yevgeniy Vorobeychik AAML 84 127 0 20 Sep 2019
Defending against Machine Learning based Inference Attacks via Adversarial Examples: Opportunities and Challenges Jinyuan Jia Neil Zhenqiang Gong AAML SILM 89 17 0 17 Sep 2019
On the Need for Topology-Aware Generative Models for Manifold-Based Defenses Uyeong Jang Susmit Jha S. Jha AAML 83 13 0 07 Sep 2019
Additive function approximation in the brain K. Harris 91 13 0 05 Sep 2019
Implicit Deep Learning L. Ghaoui Fangda Gu Bertrand Travacca Armin Askari Alicia Y. Tsai AI4CE 84 182 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 209 578 0 17 Aug 2019
BlurNet: Defense by Filtering the Feature Maps Ravi Raju Mikko H. Lipasti AAML 87 16 0 06 Aug 2019
Graph Interpolating Activation Improves Both Natural and Robust Accuracies in Data-Efficient Deep Learning Bao Wang Stanley J. Osher AAML AI4CE 77 10 0 16 Jul 2019
A unified view on differential privacy and robustness to adversarial examples Rafael Pinot Florian Yger Cédric Gouy-Pailler Jamal Atif AAML 71 18 0 19 Jun 2019
Convergence of Adversarial Training in Overparametrized Neural Networks Ruiqi Gao Tianle Cai Haochuan Li Liwei Wang Cho-Jui Hsieh Jason D. Lee AAML 126 109 0 19 Jun 2019
Adversarial attacks on Copyright Detection Systems Parsa Saadatpanah Ali Shafahi Tom Goldstein AAML 64 33 0 17 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 117 351 0 14 Jun 2019
Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers Guang-He Lee Yang Yuan Shiyu Chang Tommi Jaakkola AAML 92 127 0 12 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 175 553 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 83 39 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 77 46 0 07 Jun 2019
Adversarial Training is a Form of Data-dependent Operator Norm Regularization Kevin Roth Yannic Kilcher Thomas Hofmann 58 13 0 04 Jun 2019
DAWN: Dynamic Adversarial Watermarking of Neural Networks S. Szyller B. Atli Samuel Marchal Nadarajah Asokan MLAU AAML 91 180 0 03 Jun 2019
Unlabeled Data Improves Adversarial Robustness Y. Carmon Aditi Raghunathan Ludwig Schmidt Percy Liang John C. Duchi 157 754 0 31 May 2019
Certifiably Robust Interpretation in Deep Learning Alexander Levine Sahil Singla Soheil Feizi FAtt AAML 114 65 0 28 May 2019
Scaleable input gradient regularization for adversarial robustness Chris Finlay Adam M. Oberman AAML 116 79 0 27 May 2019
Robust Classification using Robust Feature Augmentation Kevin Eykholt Swati Gupta Atul Prakash Amir Rahmati Pratik Vaishnavi Haizhong Zheng AAML 68 2 0 26 May 2019
Rearchitecting Classification Frameworks For Increased Robustness Varun Chandrasekaran Brian Tang Nicolas Papernot Kassem Fawaz S. Jha Xi Wu AAML OOD 105 8 0 26 May 2019
Enhancing Adversarial Defense by k-Winners-Take-All Chang Xiao Peilin Zhong Changxi Zheng AAML 101 99 0 25 May 2019
Privacy Risks of Securing Machine Learning Models against Adversarial Examples Liwei Song Reza Shokri Prateek Mittal SILM MIACV AAML 99 249 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 160 29 0 17 May 2019
Adversarial Image Translation: Unrestricted Adversarial Examples in Face Recognition Systems Kazuya Kakizaki Kosuke Yoshida AAML CVBM 90 19 0 09 May 2019
Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas Shibani Santurkar Dimitris Tsipras Logan Engstrom Brandon Tran Aleksander Madry SILM 191 1,847 0 06 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 153 1,255 0 29 Apr 2019
Universal Lipschitz Approximation in Bounded Depth Neural Networks Jérémy E. Cohen Todd P. Huster Ravid Cohen AAML 67 23 0 09 Apr 2019
Minimum Uncertainty Based Detection of Adversaries in Deep Neural Networks Fatemeh Sheikholeslami Swayambhoo Jain G. Giannakis AAML 74 25 0 05 Apr 2019
HopSkipJumpAttack: A Query-Efficient Decision-Based Attack Jianbo Chen Michael I. Jordan Martin J. Wainwright AAML 159 672 0 03 Apr 2019
Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness J. Jacobsen Jens Behrmann Nicholas Carlini Florian Tramèr Nicolas Papernot AAML 84 46 0 25 Mar 2019
Robust Neural Networks using Randomized Adversarial Training Alexandre Araujo Laurent Meunier Rafael Pinot Benjamin Négrevergne AAML OOD 61 36 0 25 Mar 2019
A Research Agenda: Dynamic Models to Defend Against Correlated Attacks Ian Goodfellow AAML OOD 85 32 0 14 Mar 2019
Statistical Guarantees for the Robustness of Bayesian Neural Networks L. Cardelli Marta Kwiatkowska Luca Laurenti Nicola Paoletti A. Patané Matthew Wicker AAML 96 54 0 05 Mar 2019