Papers citing 'Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach'

Title
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-AwarenessJournal of machine learning research (JMLR), 2022 J. Liu Shreyas Padhy Jie Jessie Ren Zi Lin Yeming Wen Ghassen Jerfel Zachary Nado Jasper Snoek Dustin Tran Balaji Lakshminarayanan UQCV BDL 440 62 0 01 May 2022
Testing robustness of predictions of trained classifiers against naturally occurring perturbations S. Scher A. Trugler OOD AAML 265 3 0 21 Apr 2022
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization PerspectiveInternational Conference on Learning Representations (ICLR), 2022 Yimeng Zhang Yuguang Yao Jinghan Jia Jinfeng Yi Min-Fong Hong Shiyu Chang Sijia Liu AAML 272 39 0 27 Mar 2022
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and MethodologiesPattern Recognition (Pattern Recogn.), 2022 Zhuang Qian Kaizhu Huang Qiufeng Wang Xu-Yao Zhang OOD AAML ObjD 191 89 0 26 Mar 2022
On the sensitivity of pose estimation neural networks: rotation parameterizations, Lipschitz constants, and provable bounds Trevor Avant K. Morgansen 61 2 0 16 Mar 2022
A Survey of Adversarial Defences and Robustness in NLP Shreyansh Goyal Sumanth Doddapaneni Mitesh M.Khapra B. Ravindran AAML 351 35 0 12 Mar 2022
Adaptative Perturbation Patterns: Realistic Adversarial Learning for Robust Intrusion DetectionFuture Internet (FI), 2022 João Vitorino Nuno Oliveira Isabel Praça AAML 114 41 0 08 Mar 2022
A Domain-Theoretic Framework for Robustness Analysis of Neural NetworksMathematical Structures in Computer Science (MSCS), 2022 Can Zhou R. A. Shaikh Yiran Li Amin Farjudian OOD 257 4 0 01 Mar 2022
Mitigating Closed-model Adversarial Examples with Bayesian Neural Modeling for Enhanced End-to-End Speech RecognitionIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022 Chao-Han Huck Yang Zeeshan Ahmed Yile Gu Joseph Szurley Roger Ren Linda Liu A. Stolcke I. Bulyko AAML 166 4 0 17 Feb 2022
Holistic Adversarial Robustness of Deep Learning ModelsAAAI Conference on Artificial Intelligence (AAAI), 2022 Pin-Yu Chen Sijia Liu AAML 317 21 0 15 Feb 2022
Excitement Surfeited Turns to Errors: Deep Learning Testing Framework Based on Excitable NeuronsInformation Sciences (Inf. Sci.), 2022 Haibo Jin Ruoxi Chen Haibin Zheng Jinyin Chen Yao Cheng Yue Yu Xianglong Liu AAML 176 6 0 12 Feb 2022
Evaluation of Neural Networks Defenses and Attacks using NDCG and Reciprocal Rank MetricsInternational Journal of Information Security (JIS), 2022 Haya Brama L. Dery Tal Grinshpoun AAML 132 9 0 10 Jan 2022
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training Chen Liu Zhichao Huang Mathieu Salzmann Tong Zhang Sabine Süsstrunk AAML 269 14 0 14 Dec 2021
Reliability Assessment and Safety Arguments for Machine Learning Components in System Assurance Yizhen Dong Wei Huang Vibhav Bharti V. Cox Alec Banks Sen Wang Xingyu Zhao S. Schewe Xiaowei Huang 193 24 0 30 Nov 2021
Resilience from Diversity: Population-based approach to harden models against adversarial attacks Jasser Jasser Ivan I. Garibay AAML 148 2 0 19 Nov 2021
Discovering and Explaining the Representation Bottleneck of DNNsInternational Conference on Learning Representations (ICLR), 2021 Huiqi Deng Qihan Ren Hao Zhang Quanshi Zhang 288 70 0 11 Nov 2021
Tightening the Approximation Error of Adversarial Risk with Auto Loss Function Search Pengfei Xia Ziqiang Li Bin Li AAML 368 3 0 09 Nov 2021
Visualizing the Emergence of Intermediate Visual Patterns in DNNs Mingjie Li Shaobo Wang Quanshi Zhang 207 11 0 05 Nov 2021
ε-weakened Robustness of Deep Neural NetworksInternational Symposium on Software Testing and Analysis (ISSTA), 2021 Pei Huang Yuting Yang Minghao Liu Fuqi Jia Feifei Ma Jian Zhang AAML 139 18 0 29 Oct 2021
AugMax: Adversarial Composition of Random Augmentations for Robust Training Haotao Wang Chaowei Xiao Jean Kossaifi Zhiding Yu Anima Anandkumar Zinan Lin 274 128 0 26 Oct 2021
Characterizing Learning Dynamics of Deep Neural Networks via Complex Networks Emanuele La Malfa G. Malfa Giuseppe Nicosia Vito Latora 121 14 0 06 Oct 2021
Trustworthy AI: From Principles to Practices Yue Liu Peng Qi Bo Liu Shuai Di Jingen Liu Jiquan Pei Jinfeng Yi Bowen Zhou 367 494 0 04 Oct 2021
Compressive Visual RepresentationsNeural Information Processing Systems (NeurIPS), 2021 Kuang-Huei Lee Anurag Arnab S. Guadarrama John F. Canny Ian S. Fischer SSL 242 52 0 27 Sep 2021
On the regularized risk of distributionally robust learning over deep neural networks Camilo A. Garcia Trillos Nicolas García Trillos OOD 245 11 0 13 Sep 2021
Lipschitz Continuity Guided Knowledge DistillationIEEE International Conference on Computer Vision (ICCV), 2021 Yuzhang Shang Bin Duan Ziliang Zong Liqiang Nie Yan Yan 157 30 0 29 Aug 2021
Interpreting Attributions and Interactions of Adversarial Attacks Xin Eric Wang Shuyu Lin Hao Zhang Yufei Zhu Quanshi Zhang AAML FAtt 123 18 0 16 Aug 2021
Neural Architecture Dilation for Adversarial Robustness Yanxi Li Zhaohui Yang Yunhe Wang Chang Xu AAML 135 25 0 16 Aug 2021
Fairness Properties of Face Recognition and Obfuscation SystemsUSENIX Security Symposium (USENIX Security), 2021 Harrison Rosenberg Brian Tang Kassem Fawaz S. Jha PICV 115 17 0 05 Aug 2021
Provable Lipschitz Certification for Generative Models Matt Jordan A. Dimakis 96 14 0 06 Jul 2021
Adversarial Machine Learning for Cybersecurity and Computer Vision: Current Developments and Challenges B. Xi AAML 75 32 0 30 Jun 2021
A Survey on Trust Metrics for Autonomous Robotic SystemsAdvances in Artificial Intelligence and Machine Learning (AAIML), 2021 Vincenzo DiLuoffo W. Michalson 127 2 0 28 Jun 2021
Improving Neural Network Robustness via Persistency of ExcitationAmerican Control Conference (ACC), 2021 Kaustubh Sridhar O. Sokolsky Insup Lee James Weimer AAML 200 21 0 03 Jun 2021
NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels Jingfeng Zhang Xilie Xu Bo Han Tongliang Liu Gang Niu Li-zhen Cui Masashi Sugiyama NoLa AAML 168 9 0 31 May 2021
LipBaB: Computing exact Lipschitz constant of ReLU networksInternational Conference on Artificial Neural Networks (ICANN), 2021 Aritra Bhowmick Meenakshi D'Souza G. S. Raghavan 113 21 0 12 May 2021
Model Error Propagation via Learned Contraction Metrics for Safe Feedback Motion Planning of Unknown SystemsIEEE Conference on Decision and Control (CDC), 2021 Glen Chou N. Ozay Dmitry Berenson 202 27 0 18 Apr 2021
Orthogonalizing Convolutional Layers with the Cayley TransformInternational Conference on Learning Representations (ICLR), 2021 Asher Trockman J. Zico Kolter 186 125 0 14 Apr 2021
Pay attention to your loss: understanding misconceptions about 1-Lipschitz neural networksNeural Information Processing Systems (NeurIPS), 2021 Louis Bethune Thibaut Boissin M. Serrurier Franck Mamalet Corentin Friedrich Alberto González Sanz 324 29 0 11 Apr 2021
Learning Lipschitz Feedback Policies from Expert Demonstrations: Closed-Loop Guarantees, Generalization and Robustness Abed AlRahman Al Makdah Vishaal Krishnan Fabio Pasqualetti 160 0 0 30 Mar 2021
Recent Advances in Large Margin LearningIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021 Yiwen Guo Changshui Zhang AAML AI4CE 236 18 0 25 Mar 2021
Attack as Defense: Characterizing Adversarial Examples using RobustnessInternational Symposium on Software Testing and Analysis (ISSTA), 2021 Zhe Zhao Guangke Chen Jingyi Wang Yiwei Yang Fu Song Jun Sun AAML 142 36 0 13 Mar 2021
A Unified Game-Theoretic Interpretation of Adversarial Robustness Jie Ren Die Zhang Yisen Wang Lu Chen Zhanpeng Zhou ... Feng He Xin Eric Wang Meng Zhou Jie Shi Quanshi Zhang AAML 232 26 0 12 Mar 2021
Abstraction and Symbolic Execution of Deep Neural Networks with Bayesian Approximation of Hidden Features Nicolas Berthier Amany Alshareef James Sharp S. Schewe Xiaowei Huang 157 10 0 05 Mar 2021
Adversarial Examples can be Effective Data Augmentation for Unsupervised Machine LearningAAAI Conference on Artificial Intelligence (AAAI), 2021 Chia-Yi Hsu Pin-Yu Chen Songtao Lu Sijia Liu Chia-Mu Yu AAML 215 11 0 02 Mar 2021
Non-Singular Adversarial Robustness of Neural NetworksIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021 Yu-Lin Tsai Chia-Yi Hsu Chia-Mu Yu Pin-Yu Chen AAML OOD 131 5 0 23 Feb 2021
Training a Resilient Q-Network against Observational InterferenceAAAI Conference on Artificial Intelligence (AAAI), 2021 Chao-Han Huck Yang I-Te Danny Hung Ouyang Yi Pin-Yu Chen OOD 189 17 0 18 Feb 2021
Modeling Extremes with d-max-decreasing Neural NetworksConference on Uncertainty in Artificial Intelligence (UAI), 2021 Ali Hasan Khalil Elkhalil Yuting Ng João M. Pereira Sina Farsiu Jose H. Blanchet Vahid Tarokh 86 7 0 17 Feb 2021
Globally-Robust Neural NetworksInternational Conference on Machine Learning (ICML), 2021 Klas Leino Zifan Wang Matt Fredrikson AAML OOD 252 143 0 16 Feb 2021
Data Quality Matters For Adversarial Training: An Empirical Study Chengyu Dong Liyuan Liu Jingbo Shang AAML 163 12 0 15 Feb 2021
SPADE: A Spectral Method for Black-Box Adversarial Robustness EvaluationInternational Conference on Machine Learning (ICML), 2021 Wuxinlin Cheng Chenhui Deng Zhiqiang Zhao Yaohui Cai Zhiru Zhang Zhuo Feng AAML 265 18 0 07 Feb 2021
Increasing the Confidence of Deep Neural Networks by Coverage AnalysisIEEE Transactions on Software Engineering (TSE), 2021 Giulio Rossolini Alessandro Biondi Giorgio Buttazzo AAML 232 19 0 28 Jan 2021