v1v2v3 (latest)

Provable defenses against adversarial examples via the convex outer adversarial polytope

2 November 2017

Eric Wong

J. Zico Kolter

AAML

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Papers citing "Provable defenses against adversarial examples via the convex outer adversarial polytope"

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Title
PaRoT: A Practical Framework for Robust Deep Neural Network TrainingNASA Formal Methods (NFM), 2020 Edward W. Ayers Francisco Eiras Majd Hawasly I. Whiteside OOD 298 19 0 07 Jan 2020
Lossless Compression of Deep Neural NetworksIntegration of AI and OR Techniques in Constraint Programming (CPAIOR), 2020 Thiago Serra Abhinav Kumar Srikumar Ramalingam 440 60 0 01 Jan 2020
Efficient Adversarial Training with Transferable Adversarial ExamplesComputer Vision and Pattern Recognition (CVPR), 2019 Haizhong Zheng Ziqi Zhang Juncheng Gu Honglak Lee A. Prakash AAML 189 124 0 27 Dec 2019
Benchmarking Adversarial Robustness Yinpeng Dong Qi-An Fu Xiao Yang Tianyu Pang Hang Su Zihao Xiao Jun Zhu AAML 154 37 0 26 Dec 2019
Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized SmoothingInternational Conference on Learning Representations (ICLR), 2019 Jinyuan Jia Xiaoyu Cao Binghui Wang Neil Zhenqiang Gong AAML 129 104 0 20 Dec 2019
Resilient Cyberphysical Systems and their Application Drivers: A Technology Roadmap Somali Chaterji Parinaz Naghizadeh Ardabili M. A. Alam S. Bagchi M. Chiang ... Tiark Rompf A. Sabharwal S. Sundaram James Weimer Jennifer Weller 213 15 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 170 18 0 19 Dec 2019
Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable BytesACM Asia Conference on Computer and Communications Security (AsiaCCS), 2019 Keane Lucas Mahmood Sharif Lujo Bauer Michael K. Reiter S. Shintre AAML 218 79 0 19 Dec 2019
$n$ -ML: Mitigating Adversarial Examples via Ensembles of Topologically Manipulated Classifiers Mahmood Sharif Lujo Bauer Michael K. Reiter AAML 100 8 0 19 Dec 2019
Constructing a provably adversarially-robust classifier from a high accuracy oneInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Grzegorz Gluch R. Urbanke AAML 74 2 0 16 Dec 2019
Statistically Robust Neural Network ClassificationConference on Uncertainty in Artificial Intelligence (UAI), 2019 Benjie Wang Stefan Webb Tom Rainforth OOD AAML 196 22 0 10 Dec 2019
Training Provably Robust Models by Polyhedral Envelope RegularizationIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2019 Chen Liu Mathieu Salzmann Sabine Süsstrunk AAML 168 9 0 10 Dec 2019
A quantum active learning algorithm for sampling against adversarial attacksNew Journal of Physics (New J. Phys.), 2019 Pablo Antonio Moreno Casares M. Martin-Delgado AAML 194 11 0 06 Dec 2019
A Survey of Black-Box Adversarial Attacks on Computer Vision Models Siddhant Bhambri Sumanyu Muku Avinash Tulasi Arun Balaji Buduru AAML VLM 226 89 0 03 Dec 2019
Cost-Aware Robust Tree Ensembles for Security Applications Yizheng Chen Shiqi Wang Weifan Jiang Asaf Cidon Suman Jana AAML OOD 315 5 0 03 Dec 2019
Proving Data-Poisoning Robustness in Decision TreesCommunications of the ACM (CACM), 2019 Samuel Drews Aws Albarghouthi Loris Dántoni 118 0 0 02 Dec 2019
Fastened CROWN: Tightened Neural Network Robustness CertificatesAAAI Conference on Artificial Intelligence (AAAI), 2019 Zhaoyang Lyu Ching-Yun Ko Zhifeng Kong Ngai Wong Dahua Lin Luca Daniel 300 70 0 02 Dec 2019
A Method for Computing Class-wise Universal Adversarial Perturbations Tejus Gupta Abhishek Sinha Nupur Kumari M. Singh Balaji Krishnamurthy AAML 87 11 0 01 Dec 2019
CAMUS: A Framework to Build Formal Specifications for Deep Perception Systems Using SimulatorsEuropean Conference on Artificial Intelligence (ECAI), 2019 Julien Girard-Satabin Guillaume Charpiat Zakaria Chihani Marc Schoenauer OOD AAML 103 3 0 25 Nov 2019
Robustness Certificates for Sparse Adversarial Attacks by Randomized AblationAAAI Conference on Artificial Intelligence (AAAI), 2019 Alexander Levine Soheil Feizi AAML 201 111 0 21 Nov 2019
Fine-grained Synthesis of Unrestricted Adversarial Examples Omid Poursaeed Tianxing Jiang Yordanos Goshu Harry Yang Serge J. Belongie Ser-Nam Lim AAML 291 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 193 6 0 20 Nov 2019
Robust Deep Neural Networks Inspired by Fuzzy Logic Minh Le OOD AAML AI4CE 274 0 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 143 2 0 17 Nov 2019
Self-supervised Adversarial TrainingIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019 Kejiang Chen Hang Zhou YueFeng Chen Xiaofeng Mao Yuhong Li Yuan He Hui Xue Weiming Zhang Nenghai Yu GAN SSL 192 25 0 15 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 210 113 0 13 Nov 2019
On Robustness to Adversarial Examples and Polynomial OptimizationNeural Information Processing Systems (NeurIPS), 2019 Pranjal Awasthi Abhratanu Dutta Aravindan Vijayaraghavan OOD AAML 156 34 0 12 Nov 2019
Robust Design of Deep Neural Networks against Adversarial Attacks based on Lyapunov TheoryComputer Vision and Pattern Recognition (CVPR), 2019 Arash Rahnama A. Nguyen Edward Raff AAML 108 23 0 12 Nov 2019
Adaptive versus Standard Descent Methods and Robustness Against Adversarial Examples Marc Khoury AAML 192 1 0 09 Nov 2019
Towards Large yet Imperceptible Adversarial Image Perturbations with Perceptual Color DistanceComputer Vision and Pattern Recognition (CVPR), 2019 Subrat Kishore Dutta Zhuoran Liu Martha Larson AAML 360 168 0 06 Nov 2019
Counterexample-Guided Synthesis of Perception Models and ControlAmerican Control Conference (ACC), 2019 Shromona Ghosh Yash Vardhan Pant H. Ravanbakhsh Sanjit A. Seshia 260 18 0 04 Nov 2019
Online Robustness Training for Deep Reinforcement Learning Marc Fischer M. Mirman Steven Stalder Martin Vechev OnRL 302 49 0 03 Nov 2019
MadNet: Using a MAD Optimization for Defending Against Adversarial Attacks Shai Rozenberg G. Elidan Ran El-Yaniv AAML 104 1 0 03 Nov 2019
Adversarial Music: Real World Audio Adversary Against Wake-word Detection SystemNeural Information Processing Systems (NeurIPS), 2019 Juncheng Billy Li Shuhui Qu Xinjian Li Joseph Szurley J. Zico Kolter Florian Metze AAML 299 71 0 31 Oct 2019
Enhancing Certifiable Robustness via a Deep Model Ensemble Huan Zhang Minhao Cheng Cho-Jui Hsieh 122 9 0 31 Oct 2019
Certifiable Robustness to Graph PerturbationsNeural Information Processing Systems (NeurIPS), 2019 Aleksandar Bojchevski Stephan Günnemann AAML 229 141 0 31 Oct 2019
Certified Adversarial Robustness for Deep Reinforcement LearningConference on Robot Learning (CoRL), 2019 Björn Lütjens Michael Everett Jonathan P. How AAML 178 102 0 28 Oct 2019
Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial AttacksInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Alexander Levine Soheil Feizi AAML 117 63 0 23 Oct 2019
A New Defense Against Adversarial Images: Turning a Weakness into a StrengthNeural Information Processing Systems (NeurIPS), 2019 Tao Yu Shengyuan Hu Chuan Guo Wei-Lun Chao Kilian Q. Weinberger AAML 206 111 0 16 Oct 2019
ODE guided Neural Data Augmentation Techniques for Time Series Data and its Benefits on Robustness A. Sarkar A. Raj Raghu Sesha Iyengar AAML AI4TS 195 0 0 15 Oct 2019
Notes on Margin Training and Margin p-Values for Deep Neural Network Classifiers G. Kesidis David J. Miller Zhen Xiang 91 0 0 15 Oct 2019
DeepSearch: A Simple and Effective Blackbox Attack for Deep Neural Networks Fuyuan Zhang Sankalan Pal Chowdhury M. Christakis AAML 150 8 0 14 Oct 2019
Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks David Stutz Matthias Hein Bernt Schiele AAML 281 5 0 14 Oct 2019
Probabilistic Verification and Reachability Analysis of Neural Networks via Semidefinite ProgrammingIEEE Conference on Decision and Control (CDC), 2019 Mahyar Fazlyab M. Morari George J. Pappas AAML 184 45 0 09 Oct 2019
Directional Adversarial Training for Cost Sensitive Deep Learning Classification ApplicationsEngineering applications of artificial intelligence (EAAI), 2019 M. Terzi Gian Antonio Susto Pratik Chaudhari OOD AAML 122 17 0 08 Oct 2019
Adversarial Examples for Cost-Sensitive Classifiers Mahdi Akbari Zarkesh A. Lohn Ali Movaghar SILM AAML 109 3 0 04 Oct 2019
Universal Approximation with Certified NetworksInternational Conference on Learning Representations (ICLR), 2019 Maximilian Baader M. Mirman Martin Vechev 115 23 0 30 Sep 2019
Towards Robust Direct Perception Networks for Automated Driving Chih-Hong Cheng 76 1 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 271 104 0 29 Sep 2019
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural NetworksInternational Conference on Cyberworlds (ICC), 2019 Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 203 18 0 27 Sep 2019