Adversarial Examples Are Not Bugs, They Are Features

6 May 2019

Papers citing "Adversarial Examples Are Not Bugs, They Are Features"

50 / 373 papers shown

Title
Adversarial Detection by Approximation of Ensemble Boundary T. Windeatt AAML 26 0 0 18 Nov 2022
Diagnostics for Deep Neural Networks with Automated Copy/Paste Attacks Stephen Casper K. Hariharan Dylan Hadfield-Menell AAML 26 11 0 18 Nov 2022
Towards Good Practices in Evaluating Transfer Adversarial Attacks Zhengyu Zhao Hanwei Zhang Renjue Li R. Sicre Laurent Amsaleg Michael Backes AAML 27 20 0 17 Nov 2022
Privacy Meets Explainability: A Comprehensive Impact Benchmark S. Saifullah Dominique Mercier Adriano Lucieri Andreas Dengel Sheraz Ahmed 35 14 0 08 Nov 2022
Textual Manifold-based Defense Against Natural Language Adversarial Examples D. M. Nguyen Anh Tuan Luu AAML 27 17 0 05 Nov 2022
An Adversarial Robustness Perspective on the Topology of Neural Networks Morgane Goibert Thomas Ricatte Elvis Dohmatob AAML 16 2 0 04 Nov 2022
Data Models for Dataset Drift Controls in Machine Learning With Optical Images Luis Oala Marco Aversa Gabriel Nobis Kurt Willis Yoan Neuenschwander ... E. Pomarico Wojciech Samek Roderick Murray-Smith Christoph Clausen B. Sanguinetti 33 5 0 04 Nov 2022
Benchmarking Adversarial Patch Against Aerial Detection Jiawei Lian Shaohui Mei Shun Zhang Mingyang Ma AAML 29 56 0 30 Oct 2022
Accelerating Certified Robustness Training via Knowledge Transfer Pratik Vaishnavi Kevin Eykholt Amir Rahmati 27 7 0 25 Oct 2022
Robust Self-Supervised Learning with Lie Groups Mark Ibrahim Diane Bouchacourt Ari S. Morcos SSL OOD 42 6 0 24 Oct 2022
Evolution of Neural Tangent Kernels under Benign and Adversarial Training Noel Loo Ramin Hasani Alexander Amini Daniela Rus AAML 38 13 0 21 Oct 2022
Similarity of Neural Architectures using Adversarial Attack Transferability Jaehui Hwang Dongyoon Han Byeongho Heo Song Park Sanghyuk Chun Jong-Seok Lee AAML 37 1 0 20 Oct 2022
Understanding CNN Fragility When Learning With Imbalanced Data Damien Dablain Kristen N. Jacobson C. Bellinger Mark Roberts Nitesh Chawla 34 39 0 17 Oct 2022
Towards Generating Adversarial Examples on Mixed-type Data Han Xu Menghai Pan Zhimeng Jiang Huiyuan Chen Xiaoting Li Mahashweta Das Hao Yang AAML SILM 20 0 0 17 Oct 2022
Probabilistic Categorical Adversarial Attack & Adversarial Training Han Xu Penghei He Jie Ren Yuxuan Wan Zitao Liu Hui Liu Jiliang Tang AAML SILM 33 0 0 17 Oct 2022
What can we learn about a generated image corrupting its latent representation? A. Tomczak Aarush Gupta Slobodan Ilic Nassir Navab Shadi Albarqouni GAN MedIm 30 4 0 12 Oct 2022
What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness? Nikolaos Tsilivis Julia Kempe AAML 47 18 0 11 Oct 2022
Training Debiased Subnetworks with Contrastive Weight Pruning Geon Yeong Park Sangmin Lee Sang Wan Lee Jong Chul Ye CML 40 13 0 11 Oct 2022
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization Ziquan Liu Antoni B. Chan AAML 33 5 0 11 Oct 2022
Certified Training: Small Boxes are All You Need Mark Niklas Muller Franziska Eckert Marc Fischer Martin Vechev AAML 39 46 0 10 Oct 2022
Game-Theoretic Understanding of Misclassification Kosuke Sumiyasu K. Kawamoto Hiroshi Kera 40 1 0 07 Oct 2022
Data Poisoning Attacks Against Multimodal Encoders Ziqing Yang Xinlei He Zheng Li Michael Backes Mathias Humbert Pascal Berrang Yang Zhang AAML 118 46 0 30 Sep 2022
Inducing Data Amplification Using Auxiliary Datasets in Adversarial Training Saehyung Lee Hyungyu Lee AAML 29 2 0 27 Sep 2022
Fairness and robustness in anti-causal prediction Maggie Makar Alexander DÁmour OOD 36 10 0 20 Sep 2022
Watch What You Pretrain For: Targeted, Transferable Adversarial Examples on Self-Supervised Speech Recognition models R. Olivier H. Abdullah Bhiksha Raj AAML 26 1 0 17 Sep 2022
Enhance the Visual Representation via Discrete Adversarial Training Xiaofeng Mao YueFeng Chen Ranjie Duan Yao Zhu Gege Qi Shaokai Ye Xiaodan Li Rong Zhang Hui Xue 46 31 0 16 Sep 2022
Scattering Model Guided Adversarial Examples for SAR Target Recognition: Attack and Defense Bo Peng Bo Peng Jie Zhou Jianyue Xie Li Liu AAML 40 43 0 11 Sep 2022
Saliency Guided Adversarial Training for Learning Generalizable Features with Applications to Medical Imaging Classification System Xin Li Yao Qiang Chengyin Li Sijia Liu D. Zhu OOD MedIm 39 4 0 09 Sep 2022
Unrestricted Adversarial Samples Based on Non-semantic Feature Clusters Substitution Ming-Kuai Zhou Xiaobing Pei AAML 16 0 0 31 Aug 2022
Shortcut Learning of Large Language Models in Natural Language Understanding Mengnan Du Fengxiang He Na Zou Dacheng Tao Xia Hu KELM OffRL 42 84 0 25 Aug 2022
Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks Tilman Raukur A. Ho Stephen Casper Dylan Hadfield-Menell AAML AI4CE 28 124 0 27 Jul 2022
Improving Adversarial Robustness via Mutual Information Estimation Dawei Zhou Nannan Wang Xinbo Gao Bo Han Xiaoyu Wang Yibing Zhan Tongliang Liu AAML 19 15 0 25 Jul 2022
Can we achieve robustness from data alone? Nikolaos Tsilivis Jingtong Su Julia Kempe OOD DD 38 18 0 24 Jul 2022
Decorrelative Network Architecture for Robust Electrocardiogram Classification Christopher Wiedeman Ge Wang OOD 13 2 0 19 Jul 2022
On the Robustness and Anomaly Detection of Sparse Neural Networks Morgane Ayle Bertrand Charpentier John Rachwan Daniel Zügner Simon Geisler Stephan Günnemann AAML 60 3 0 09 Jul 2022
How many perturbations break this model? Evaluating robustness beyond adversarial accuracy R. Olivier Bhiksha Raj AAML 34 5 0 08 Jul 2022
Removing Batch Normalization Boosts Adversarial Training Haotao Wang Aston Zhang Shuai Zheng Xingjian Shi Mu Li Zhangyang Wang 40 42 0 04 Jul 2022
Efficient Adversarial Training With Data Pruning Maximilian Kaufmann Yiren Zhao Ilia Shumailov Robert D. Mullins Nicolas Papernot AAML 42 7 0 01 Jul 2022
Auditing Visualizations: Transparency Methods Struggle to Detect Anomalous Behavior Jean-Stanislas Denain Jacob Steinhardt AAML 44 7 0 27 Jun 2022
Robustness Evaluation of Deep Unsupervised Learning Algorithms for Intrusion Detection Systems D'Jeff K. Nkashama Ariana Soltani Jean-Charles Verdier Marc Frappier Pierre-Marting Tardif F. Kabanza OOD AAML 29 5 0 25 Jun 2022
On the Role of Generalization in Transferability of Adversarial Examples Yilin Wang Farzan Farnia AAML 24 10 0 18 Jun 2022
A Meta-Analysis of Distributionally-Robust Models Ben Feuer Ameya Joshi C. Hegde OOD VLM 43 3 0 15 Jun 2022
SeATrans: Learning Segmentation-Assisted diagnosis model via Transformer Junde Wu Huihui Fang Fangxin Shang Dalu Yang Zhao-Yang Wang Jing Gao Yehui Yang Yanwu Xu MedIm ViT 37 19 0 12 Jun 2022
Meet You Halfway: Explaining Deep Learning Mysteries Oriel BenShmuel AAML FedML FAtt OOD 30 0 0 09 Jun 2022
Adversarial Reprogramming Revisited Matthias Englert R. Lazic AAML 29 9 0 07 Jun 2022
Building Robust Ensembles via Margin Boosting Dinghuai Zhang Hongyang R. Zhang Aaron Courville Yoshua Bengio Pradeep Ravikumar A. Suggala AAML UQCV 48 15 0 07 Jun 2022
Vanilla Feature Distillation for Improving the Accuracy-Robustness Trade-Off in Adversarial Training Guodong Cao Peng Kuang Xiaowei Dong Zhifei Zhang Hengchang Guo Zhan Qin Kui Ren AAML 30 1 0 05 Jun 2022
Optimizing Relevance Maps of Vision Transformers Improves Robustness Hila Chefer Idan Schwartz Lior Wolf ViT 40 38 0 02 Jun 2022
Exact Feature Collisions in Neural Networks Utku Ozbulak Manvel Gasparyan Shodhan Rao W. D. Neve Arnout Van Messem AAML 27 1 0 31 May 2022
An Analytic Framework for Robust Training of Artificial Neural Networks R. Barati Reza Safabakhsh Mohammad Rahmati AAML 19 0 0 26 May 2022