Provable defenses against adversarial examples via the convex outer adversarial polytope

2 November 2017

J. Zico Kolter

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

50 / 386 papers shown

Title
Quantum noise protects quantum classifiers against adversaries Yuxuan Du Min-hsiu Hsieh Tongliang Liu Dacheng Tao Nana Liu AAML 22 110 0 20 Mar 2020
Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations Huan Zhang Hongge Chen Chaowei Xiao Bo-wen Li Mingyan D. Liu Duane S. Boning Cho-Jui Hsieh AAML 44 261 0 19 Mar 2020
Diversity can be Transferred: Output Diversification for White- and Black-box Attacks Y. Tashiro Yang Song Stefano Ermon AAML 14 13 0 15 Mar 2020
Topological Effects on Attacks Against Vertex Classification B. A. Miller Mustafa Çamurcu Alexander J. Gomez Kevin S. Chan Tina Eliassi-Rad AAML 19 2 0 12 Mar 2020
Exploiting Verified Neural Networks via Floating Point Numerical Error Kai Jia Martin Rinard AAML 37 34 0 06 Mar 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 47 787 0 26 Feb 2020
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger Jingfeng Zhang Xilie Xu Bo Han Gang Niu Li-zhen Cui Masashi Sugiyama Mohan S. Kankanhalli AAML 33 397 0 26 Feb 2020
Lagrangian Decomposition for Neural Network Verification Rudy Bunel Alessandro De Palma Alban Desmaison Krishnamurthy Dvijotham Pushmeet Kohli Philip Torr M. P. Kumar 19 50 0 24 Feb 2020
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh 24 78 0 24 Feb 2020
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework Dinghuai Zhang Mao Ye Chengyue Gong Zhanxing Zhu Qiang Liu AAML 24 62 0 21 Feb 2020
Indirect Adversarial Attacks via Poisoning Neighbors for Graph Convolutional Networks Tsubasa Takahashi GNN AAML 19 37 0 19 Feb 2020
Deflecting Adversarial Attacks Yao Qin Nicholas Frosst Colin Raffel G. Cottrell Geoffrey E. Hinton AAML 30 15 0 18 Feb 2020
Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality Yi Zhang Orestis Plevrakis S. Du Xingguo Li Zhao Song Sanjeev Arora 29 51 0 16 Feb 2020
Robustness Verification for Transformers Zhouxing Shi Huan Zhang Kai-Wei Chang Minlie Huang Cho-Jui Hsieh AAML 24 105 0 16 Feb 2020
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models Lin Chen Yifei Min Mingrui Zhang Amin Karbasi OOD 38 64 0 11 Feb 2020
Adversarial Robustness for Code Pavol Bielik Martin Vechev AAML 22 89 0 11 Feb 2020
Semialgebraic Optimization for Lipschitz Constants of ReLU Networks Tong Chen J. Lasserre Victor Magron Edouard Pauwels 36 3 0 10 Feb 2020
Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness Aounon Kumar Alexander Levine Tom Goldstein S. Feizi 15 94 0 08 Feb 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 28 80 0 22 Jan 2020
GhostImage: Remote Perception Attacks against Camera-based Image Classification Systems Yanmao Man Ming Li Ryan M. Gerdes AAML 22 8 0 21 Jan 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 99 1,159 0 12 Jan 2020
ReluDiff: Differential Verification of Deep Neural Networks Brandon Paulsen Jingbo Wang Chao Wang 27 53 0 10 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 21 177 0 08 Jan 2020
Lossless Compression of Deep Neural Networks Thiago Serra Abhinav Kumar Srikumar Ramalingam 24 56 0 01 Jan 2020
Efficient Adversarial Training with Transferable Adversarial Examples Haizhong Zheng Ziqi Zhang Juncheng Gu Honglak Lee A. Prakash AAML 24 108 0 27 Dec 2019
Benchmarking Adversarial Robustness Yinpeng Dong Qi-An Fu Xiao Yang Tianyu Pang Hang Su Zihao Xiao Jun Zhu AAML 31 36 0 26 Dec 2019
Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable Bytes Keane Lucas Mahmood Sharif Lujo Bauer Michael K. Reiter S. Shintre AAML 31 66 0 19 Dec 2019
Robustness Certificates for Sparse Adversarial Attacks by Randomized Ablation Alexander Levine S. Feizi AAML 34 104 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 37 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
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 21 104 0 13 Nov 2019
Towards Large yet Imperceptible Adversarial Image Perturbations with Perceptual Color Distance Zhengyu Zhao Zhuoran Liu Martha Larson AAML 18 142 0 06 Nov 2019
Counterexample-Guided Synthesis of Perception Models and Control Shromona Ghosh Yash Vardhan Pant H. Ravanbakhsh S. Seshia 35 14 0 04 Nov 2019
Enhancing Certifiable Robustness via a Deep Model Ensemble Huan Zhang Minhao Cheng Cho-Jui Hsieh 33 9 0 31 Oct 2019
A New Defense Against Adversarial Images: Turning a Weakness into a Strength Tao Yu Shengyuan Hu Chuan Guo Wei-Lun Chao Kilian Q. Weinberger AAML 58 101 0 16 Oct 2019
Probabilistic Verification and Reachability Analysis of Neural Networks via Semidefinite Programming Mahyar Fazlyab M. Morari George J. Pappas AAML 35 41 0 09 Oct 2019
Adversarial Examples for Cost-Sensitive Classifiers Mahdi Akbari Zarkesh A. Lohn Ali Movaghar SILM AAML 24 3 0 04 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
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 24 18 0 27 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 25 125 0 20 Sep 2019
Implicit Deep Learning L. Ghaoui Fangda Gu Bertrand Travacca Armin Askari Alicia Y. Tsai AI4CE 34 176 0 17 Aug 2019
Adversarial shape perturbations on 3D point clouds Daniel Liu Ronald Yu Hao Su 3DPC 33 12 0 16 Aug 2019
ART: Abstraction Refinement-Guided Training for Provably Correct Neural Networks Xuankang Lin He Zhu R. Samanta Suresh Jagannathan AAML 27 28 0 17 Jul 2019
Accurate, reliable and fast robustness evaluation Wieland Brendel Jonas Rauber Matthias Kümmerer Ivan Ustyuzhaninov Matthias Bethge AAML OOD 13 113 0 01 Jul 2019
Certifiable Robustness and Robust Training for Graph Convolutional Networks Daniel Zügner Stephan Günnemann OffRL 39 162 0 28 Jun 2019
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness Fanny Yang Zuowen Wang C. Heinze-Deml 28 42 0 26 Jun 2019
Quantitative Verification of Neural Networks And its Security Applications Teodora Baluta Shiqi Shen Shweta Shinde Kuldeep S. Meel P. Saxena AAML 21 104 0 25 Jun 2019
Evaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective Lu Wang Xuanqing Liu Jinfeng Yi Zhi-Hua Zhou Cho-Jui Hsieh AAML 28 22 0 10 Jun 2019
Robustness Verification of Tree-based Models Hongge Chen Huan Zhang Si Si Yang Li Duane S. Boning Cho-Jui Hsieh AAML 17 76 0 10 Jun 2019