Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation

23 May 2017

Matthias Hein

Papers citing "Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation"

50 / 119 papers shown

Title
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 32 65 0 09 Apr 2021
A Review of Formal Methods applied to Machine Learning Caterina Urban Antoine Miné 39 55 0 06 Apr 2021
A Unified Game-Theoretic Interpretation of Adversarial Robustness Jie Ren Die Zhang Yisen Wang Lu Chen Zhanpeng Zhou ... Xu Cheng Xin Wang Meng Zhou Jie Shi Quanshi Zhang AAML 72 22 0 12 Mar 2021
Non-Singular Adversarial Robustness of Neural Networks Yu-Lin Tsai Chia-Yi Hsu Chia-Mu Yu Pin-Yu Chen AAML OOD 9 5 0 23 Feb 2021
Fast Training of Provably Robust Neural Networks by SingleProp Akhilan Boopathy Tsui-Wei Weng Sijia Liu Pin-Yu Chen Gaoyuan Zhang Luca Daniel AAML 11 7 0 01 Feb 2021
Increasing the Confidence of Deep Neural Networks by Coverage Analysis Giulio Rossolini Alessandro Biondi Giorgio Buttazzo AAML 26 13 0 28 Jan 2021
ROBY: Evaluating the Robustness of a Deep Model by its Decision Boundaries Jinyin Chen Zhen Wang Haibin Zheng Jun Xiao Zhaoyan Ming AAML 13 5 0 18 Dec 2020
Feature Space Singularity for Out-of-Distribution Detection Haiwen Huang Zhihan Li Lulu Wang Sishuo Chen Bin Dong Xinyu Zhou OODD 22 65 0 30 Nov 2020
A Study on the Uncertainty of Convolutional Layers in Deep Neural Networks Hao Shen Sihong Chen Ran Wang 30 5 0 27 Nov 2020
Adversarially Robust Classification based on GLRT Bhagyashree Puranik Upamanyu Madhow Ramtin Pedarsani VLM AAML 18 4 0 16 Nov 2020
Characterizing and Taming Model Instability Across Edge Devices Eyal Cidon Evgenya Pergament Zain Asgar Asaf Cidon Sachin Katti 14 7 0 18 Oct 2020
Input Hessian Regularization of Neural Networks Waleed Mustafa Robert A. Vandermeulen Marius Kloft AAML 19 12 0 14 Sep 2020
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Bo-wen Li AAML 30 128 0 09 Sep 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 25 73 0 07 Aug 2020
A Le Cam Type Bound for Adversarial Learning and Applications Qiuling Xu Kevin Bello Jean Honorio AAML 16 1 0 01 Jul 2020
Counterexample-Guided Learning of Monotonic Neural Networks Aishwarya Sivaraman G. Farnadi T. Millstein Guy Van den Broeck 24 50 0 16 Jun 2020
Calibrated Surrogate Losses for Adversarially Robust Classification Han Bao Clayton Scott Masashi Sugiyama 27 45 0 28 May 2020
Training robust neural networks using Lipschitz bounds Patricia Pauli Anne Koch J. Berberich Paul Kohler Frank Allgöwer 19 156 0 06 May 2020
Verification of Deep Convolutional Neural Networks Using ImageStars Hoang-Dung Tran Stanley Bak Weiming Xiang Taylor T. Johnson AAML 20 127 0 12 Apr 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability Maximilian Augustin Alexander Meinke Matthias Hein OOD 75 98 0 20 Mar 2020
When are Non-Parametric Methods Robust? Robi Bhattacharjee Kamalika Chaudhuri AAML 36 28 0 13 Mar 2020
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness Ahmadreza Jeddi M. Shafiee Michelle Karg C. Scharfenberger A. Wong OOD AAML 58 63 0 02 Mar 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 27 396 0 26 Feb 2020
Robustness Verification for Transformers Zhouxing Shi Huan Zhang Kai-Wei Chang Minlie Huang Cho-Jui Hsieh AAML 19 104 0 16 Feb 2020
Efficient Adversarial Training with Transferable Adversarial Examples Haizhong Zheng Ziqi Zhang Juncheng Gu Honglak Lee A. Prakash AAML 22 108 0 27 Dec 2019
Benchmarking Adversarial Robustness Yinpeng Dong Qi-An Fu Xiao Yang Tianyu Pang Hang Su Zihao Xiao Jun Zhu AAML 28 36 0 26 Dec 2019
There is Limited Correlation between Coverage and Robustness for Deep Neural Networks Yizhen Dong Peixin Zhang Jingyi Wang Shuang Liu Jun Sun Jianye Hao Xinyu Wang Li Wang J. Dong Ting Dai OOD AAML 19 32 0 14 Nov 2019
Enhancing Certifiable Robustness via a Deep Model Ensemble Huan Zhang Minhao Cheng Cho-Jui Hsieh 33 9 0 31 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
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 24 139 0 26 Sep 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack Francesco Croce Matthias Hein AAML 40 474 0 03 Jul 2019
Robustness Guarantees for Deep Neural Networks on Videos Min Wu Marta Z. Kwiatkowska AAML 17 22 0 28 Jun 2019
Certifiable Robustness and Robust Training for Graph Convolutional Networks Daniel Zügner Stephan Günnemann OffRL 31 160 0 28 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 25 35 0 09 Jun 2019
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks Maksym Andriushchenko Matthias Hein 20 61 0 08 Jun 2019
Robustness for Non-Parametric Classification: A Generic Attack and Defense Yao-Yuan Yang Cyrus Rashtchian Yizhen Wang Kamalika Chaudhuri SILM AAML 34 42 0 07 Jun 2019
Controlling Neural Level Sets Matan Atzmon Niv Haim Lior Yariv Ofer Israelov Haggai Maron Y. Lipman AI4CE 22 118 0 28 May 2019
Scaleable input gradient regularization for adversarial robustness Chris Finlay Adam M. Oberman AAML 16 77 0 27 May 2019
POPQORN: Quantifying Robustness of Recurrent Neural Networks Ching-Yun Ko Zhaoyang Lyu Tsui-Wei Weng Luca Daniel Ngai Wong Dahua Lin AAML 17 75 0 17 May 2019
Virtual Mixup Training for Unsupervised Domain Adaptation Xudong Mao Yun Ma Zhenguo Yang Yangbin Chen Qing Li 35 52 0 10 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 35 1,227 0 29 Apr 2019
Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks Francesco Croce Jonas Rauber Matthias Hein AAML 20 30 0 27 Mar 2019
PROVEN: Certifying Robustness of Neural Networks with a Probabilistic Approach Tsui-Wei Weng Pin-Yu Chen Lam M. Nguyen M. Squillante Ivan V. Oseledets Luca Daniel AAML 13 30 0 18 Dec 2018
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 40 552 0 13 Dec 2018
MMA Training: Direct Input Space Margin Maximization through Adversarial Training G. Ding Yash Sharma Kry Yik-Chau Lui Ruitong Huang AAML 16 270 0 06 Dec 2018
Prototype-based Neural Network Layers: Incorporating Vector Quantization S. Saralajew Lars Holdijk Maike Rees T. Villmann MQ 17 15 0 04 Dec 2018
A randomized gradient-free attack on ReLU networks Francesco Croce Matthias Hein AAML 34 21 0 28 Nov 2018
Robustness via curvature regularization, and vice versa Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi J. Uesato P. Frossard AAML 23 318 0 23 Nov 2018
Theoretical Analysis of Adversarial Learning: A Minimax Approach Zhuozhuo Tu Jingwei Zhang Dacheng Tao AAML 13 68 0 13 Nov 2018