A Boundary Tilting Persepective on the Phenomenon of Adversarial Examples

27 August 2016

Papers citing "A Boundary Tilting Persepective on the Phenomenon of Adversarial Examples"

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Title
Towards Label-Only Membership Inference Attack against Pre-trained Large Language Models Yu He Boheng Li Lu Liu Zhongjie Ba Wei Dong Yiming Li Zengchang Qin Kui Ren Chong Chen MIALM 79 0 0 26 Feb 2025
A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs Kasimir Tanner Matteo Vilucchio Bruno Loureiro Florent Krzakala AAML 68 0 0 31 Dec 2024
Exploiting the Layered Intrinsic Dimensionality of Deep Models for Practical Adversarial Training Enes Altinisik Safa Messaoud Husrev Taha Sencar Hassan Sajjad Sanjay Chawla AAML 53 0 0 27 May 2024
Training Image Derivatives: Increased Accuracy and Universal Robustness V. Avrutskiy 51 0 0 21 Oct 2023
Assessing Privacy Risks in Language Models: A Case Study on Summarization Tasks Ruixiang Tang Gord Lueck Rodolfo Quispe Huseyin A. Inan Janardhan Kulkarni Xia Hu 34 6 0 20 Oct 2023
Improve Video Representation with Temporal Adversarial Augmentation Jinhao Duan Quanfu Fan Hao-Ran Cheng Xiaoshuang Shi Kaidi Xu AAML AI4TS ViT 33 2 0 28 Apr 2023
It Is All About Data: A Survey on the Effects of Data on Adversarial Robustness Peiyu Xiong Michael W. Tegegn Jaskeerat Singh Sarin Shubhraneel Pal Julia Rubin SILM AAML 37 8 0 17 Mar 2023
Linking convolutional kernel size to generalization bias in face analysis CNNs Hao Liang J. O. Caro Vikram Maheshri Ankit B. Patel Guha Balakrishnan CVBM CML 23 0 0 07 Feb 2023
Identifying Adversarially Attackable and Robust Samples Vyas Raina Mark Gales AAML 38 3 0 30 Jan 2023
REAP: A Large-Scale Realistic Adversarial Patch Benchmark Nabeel Hingun Chawin Sitawarin Jerry Li David Wagner AAML 31 14 0 12 Dec 2022
Textual Manifold-based Defense Against Natural Language Adversarial Examples D. M. Nguyen Anh Tuan Luu AAML 29 17 0 05 Nov 2022
Scattering Model Guided Adversarial Examples for SAR Target Recognition: Attack and Defense Bo Peng Bo Peng Jie Zhou Jianyue Xie Li Liu AAML 50 43 0 11 Sep 2022
An Analytic Framework for Robust Training of Artificial Neural Networks R. Barati Reza Safabakhsh Mohammad Rahmati AAML 19 0 0 26 May 2022
A Manifold View of Adversarial Risk Wen-jun Zhang Yikai Zhang Xiaoling Hu Mayank Goswami Chao Chen Dimitris N. Metaxas AAML 19 6 0 24 Mar 2022
Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data Yaoqing Yang Ryan Theisen Liam Hodgkinson Joseph E. Gonzalez Kannan Ramchandran Charles H. Martin Michael W. Mahoney 97 17 0 06 Feb 2022
Image classifiers can not be made robust to small perturbations Zheng Dai David K Gifford VLM AAML 36 1 0 07 Dec 2021
Sparse Adversarial Video Attacks with Spatial Transformations Ronghui Mu Wenjie Ruan Leandro Soriano Marcolino Q. Ni AAML 35 18 0 10 Nov 2021
A novel network training approach for open set image recognition Md Tahmid Hossaina S. Teng Guojun Lu Ferdous Sohel 26 0 0 27 Sep 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Mian Navid Kardan M. Shah AAML 41 236 0 01 Aug 2021
Scale-invariant scale-channel networks: Deep networks that generalise to previously unseen scales Ylva Jansson T. Lindeberg 13 23 0 11 Jun 2021
Do Input Gradients Highlight Discriminative Features? Harshay Shah Prateek Jain Praneeth Netrapalli AAML FAtt 31 57 0 25 Feb 2021
ROBY: Evaluating the Robustness of a Deep Model by its Decision Boundaries Jinyin Chen Zhen Wang Haibin Zheng Jun Xiao Zhaoyan Ming AAML 27 5 0 18 Dec 2020
Unsupervised Adversarially-Robust Representation Learning on Graphs Jiarong Xu Yang Yang Junru Chen Chunping Wang Xin Jiang Jiangang Lu Yizhou Sun SSL AAML OOD 38 36 0 04 Dec 2020
Visually Imperceptible Adversarial Patch Attacks on Digital Images Yaguan Qian Jiamin Wang Bin Wang Xiang Ling Zhaoquan Gu Chunming Wu Wassim Swaileh AAML 44 2 0 02 Dec 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
A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning Hongjun Wang Guanbin Li Xiaobai Liu Liang Lin GAN AAML 21 22 0 15 Oct 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 46 62 0 11 Sep 2020
Quantifying the Preferential Direction of the Model Gradient in Adversarial Training With Projected Gradient Descent Ricardo Bigolin Lanfredi Joyce D. Schroeder Tolga Tasdizen 27 11 0 10 Sep 2020
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective G. R. Machado Eugênio Silva R. Goldschmidt AAML 33 157 0 08 Sep 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 32 73 0 07 Aug 2020
Understanding Adversarial Examples from the Mutual Influence of Images and Perturbations Chaoning Zhang Philipp Benz Tooba Imtiaz In-So Kweon SSL AAML 22 118 0 13 Jul 2020
Boundary thickness and robustness in learning models Yaoqing Yang Rekha Khanna Yaodong Yu A. Gholami Kurt Keutzer Joseph E. Gonzalez Kannan Ramchandran Michael W. Mahoney OOD 18 37 0 09 Jul 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 39 148 0 20 May 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 72 63 0 02 Mar 2020
Softmax-based Classification is k-means Clustering: Formal Proof, Consequences for Adversarial Attacks, and Improvement through Centroid Based Tailoring Sibylle Hess W. Duivesteijn Decebal Constantin Mocanu 25 12 0 07 Jan 2020
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 29 18 0 27 Sep 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 23 230 0 24 Jul 2019
PhysGAN: Generating Physical-World-Resilient Adversarial Examples for Autonomous Driving Zelun Kong Junfeng Guo Ang Li Cong Liu AAML 41 126 0 09 Jul 2019
Adversarial Robustness via Label-Smoothing Morgane Goibert Elvis Dohmatob AAML 10 18 0 27 Jun 2019
ML-LOO: Detecting Adversarial Examples with Feature Attribution Puyudi Yang Jianbo Chen Cho-Jui Hsieh Jane-ling Wang Michael I. Jordan AAML 22 101 0 08 Jun 2019
Provably scale-covariant continuous hierarchical networks based on scale-normalized differential expressions coupled in cascade T. Lindeberg 27 19 0 29 May 2019
What Do Adversarially Robust Models Look At? Takahiro Itazuri Yoshihiro Fukuhara Hirokatsu Kataoka Shigeo Morishima 19 5 0 19 May 2019
Bridging Adversarial Robustness and Gradient Interpretability Beomsu Kim Junghoon Seo Taegyun Jeon AAML 22 39 0 27 Mar 2019
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations Saeid Asgari Taghanaki Kumar Abhishek Shekoofeh Azizi Ghassan Hamarneh AAML 31 40 0 03 Mar 2019
An Information-Theoretic Explanation for the Adversarial Fragility of AI Classifiers Hui Xie Jirong Yi Weiyu Xu R. Mudumbai AAML 29 3 0 27 Jan 2019
Defending Against Universal Perturbations With Shared Adversarial Training Chaithanya Kumar Mummadi Thomas Brox J. H. Metzen AAML 18 60 0 10 Dec 2018
Robustness via curvature regularization, and vice versa Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi J. Uesato P. Frossard AAML 29 318 0 23 Nov 2018
Structured Adversarial Attack: Towards General Implementation and Better Interpretability Kaidi Xu Sijia Liu Pu Zhao Pin-Yu Chen Huan Zhang Quanfu Fan Deniz Erdogmus Yanzhi Wang Xinyu Lin AAML 29 160 0 05 Aug 2018
With Friends Like These, Who Needs Adversaries? Saumya Jetley Nicholas A. Lord Philip Torr AAML 21 70 0 11 Jul 2018
Understanding Measures of Uncertainty for Adversarial Example Detection Lewis Smith Y. Gal UQCV 57 358 0 22 Mar 2018