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 / 1,327 papers shown

Title
Square Attack: a query-efficient black-box adversarial attack via random search Maksym Andriushchenko Francesco Croce Nicolas Flammarion Matthias Hein AAML 291 1,049 0 29 Nov 2019
Fantastic Four: Differentiable Bounds on Singular Values of Convolution Layers Sahil Singla Soheil Feizi AAML 83 8 0 22 Nov 2019
Robustness Certificates for Sparse Adversarial Attacks by Randomized Ablation Alexander Levine Soheil Feizi AAML 97 108 0 21 Nov 2019
The Origins and Prevalence of Texture Bias in Convolutional Neural Networks Katherine L. Hermann Ting Chen Simon Kornblith CVBM 127 21 0 20 Nov 2019
Fine-grained Synthesis of Unrestricted Adversarial Examples Omid Poursaeed Tianxing Jiang Yordanos Goshu Harry Yang Serge J. Belongie Ser-Nam Lim AAML 138 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 141 6 0 20 Nov 2019
Smoothed Inference for Adversarially-Trained Models Yaniv Nemcovsky Evgenii Zheltonozhskii Chaim Baskin Brian Chmiel Maxim Fishman A. Bronstein A. Mendelson AAML FedML 59 2 0 17 Nov 2019
Robust Design of Deep Neural Networks against Adversarial Attacks based on Lyapunov Theory Arash Rahnama A. Nguyen Edward Raff AAML 68 21 0 12 Nov 2019
Towards Large yet Imperceptible Adversarial Image Perturbations with Perceptual Color Distance Subrat Kishore Dutta Zhuoran Liu Martha Larson AAML 179 156 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 201 116 0 03 Nov 2019
MadNet: Using a MAD Optimization for Defending Against Adversarial Attacks Shai Rozenberg G. Elidan Ran El-Yaniv AAML 53 1 0 03 Nov 2019
Certified Adversarial Robustness for Deep Reinforcement Learning Björn Lütjens Michael Everett Jonathan P. How AAML 165 100 0 28 Oct 2019
Diametrical Risk Minimization: Theory and Computations Matthew Norton J. Royset 136 19 0 24 Oct 2019
Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial Attacks Alexander Levine Soheil Feizi AAML 77 61 0 23 Oct 2019
Structure Matters: Towards Generating Transferable Adversarial Images Dan Peng Zizhan Zheng Linhao Luo Xiaofeng Zhang AAML 97 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 138 68 0 18 Oct 2019
Extracting robust and accurate features via a robust information bottleneck Ankit Pensia Varun Jog Po-Ling Loh AAML 90 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 150 42 0 05 Oct 2019
Adversarial Examples for Cost-Sensitive Classifiers Mahdi Akbari Zarkesh A. Lohn Ali Movaghar SILM AAML 65 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 165 34 0 01 Oct 2019
Universal Approximation with Certified Networks Maximilian Baader M. Mirman Martin Vechev 88 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 165 100 0 29 Sep 2019
Towards neural networks that provably know when they don't know Alexander Meinke Matthias Hein OODD 152 143 0 26 Sep 2019
FENCE: Feasible Evasion Attacks on Neural Networks in Constrained Environments Alesia Chernikova Alina Oprea AAML 228 44 0 23 Sep 2019
Defending Against Physically Realizable Attacks on Image Classification Tong Wu Liang Tong Yevgeniy Vorobeychik AAML 120 132 0 20 Sep 2019
Defending against Machine Learning based Inference Attacks via Adversarial Examples: Opportunities and Challenges Jinyuan Jia Neil Zhenqiang Gong AAML SILM 101 18 0 17 Sep 2019
On the Need for Topology-Aware Generative Models for Manifold-Based Defenses Uyeong Jang Susmit Jha S. Jha AAML 89 13 0 07 Sep 2019
Additive function approximation in the brain K. Harris 109 13 0 05 Sep 2019
Implicit Deep Learning L. Ghaoui Fangda Gu Bertrand Travacca Armin Askari Alicia Y. Tsai AI4CE 173 187 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 337 611 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 75 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 168 111 0 19 Jun 2019
Adversarial attacks on Copyright Detection Systems Parsa Saadatpanah Ali Shafahi Tom Goldstein AAML 74 36 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 192 357 0 14 Jun 2019
Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers Guang-He Lee Yang Yuan Shiyu Chang Tommi Jaakkola AAML 114 127 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 311 565 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 145 40 0 09 Jun 2019
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks Maksym Andriushchenko Matthias Hein 102 64 0 08 Jun 2019
Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robustness Walt Woods Jack H Chen C. Teuscher AAML 145 46 0 07 Jun 2019
Adversarial Training is a Form of Data-dependent Operator Norm Regularization Kevin Roth Yannic Kilcher Thomas Hofmann 62 13 0 04 Jun 2019
DAWN: Dynamic Adversarial Watermarking of Neural Networks S. Szyller B. Atli Samuel Marchal Nadarajah Asokan MLAU AAML 127 186 0 03 Jun 2019
Unlabeled Data Improves Adversarial Robustness Y. Carmon Aditi Raghunathan Ludwig Schmidt Percy Liang John C. Duchi 246 765 0 31 May 2019
Certifiably Robust Interpretation in Deep Learning Alexander Levine Sahil Singla Soheil Feizi FAtt AAML 193 65 0 28 May 2019
Scaleable input gradient regularization for adversarial robustness Chris Finlay Adam M. Oberman AAML 134 81 0 27 May 2019
Robust Classification using Robust Feature Augmentation Kevin Eykholt Swati Gupta Atul Prakash Amir Rahmati Pratik Vaishnavi Haizhong Zheng AAML 80 2 0 26 May 2019