Adversarial vulnerability for any classifier

23 February 2018

Papers citing "Adversarial vulnerability for any classifier"

45 / 45 papers shown

Title
Adversarial Detection with a Dynamically Stable System Xiaowei Long Jie Lin Xiangyuan Yang AAML 36 0 0 11 Nov 2024
Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers Jonas Ngnawé Sabyasachi Sahoo Y. Pequignot Frédéric Precioso Christian Gagné AAML 39 0 0 26 Jun 2024
On The Relationship Between Universal Adversarial Attacks And Sparse Representations Dana Weitzner Raja Giryes AAML 24 0 0 14 Nov 2023
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness Ambar Pal Huaijin Hao René Vidal 26 8 0 28 Sep 2023
Exploiting Frequency Spectrum of Adversarial Images for General Robustness Chun Yang Tan K. Kawamoto Hiroshi Kera AAML OOD 26 1 0 15 May 2023
When are Local Queries Useful for Robust Learning? Pascale Gourdeau Varun Kanade Marta Z. Kwiatkowska J. Worrell OOD 33 1 0 12 Oct 2022
Defense Against Multi-target Trojan Attacks Haripriya Harikumar Santu Rana Kien Do Sunil R. Gupta W. Zong Willy Susilo Svetha Venkatesh AAML 6 3 0 08 Jul 2022
Sample Complexity Bounds for Robustly Learning Decision Lists against Evasion Attacks Pascale Gourdeau Varun Kanade Marta Z. Kwiatkowska J. Worrell AAML 13 5 0 12 May 2022
A Manifold View of Adversarial Risk Wen-jun Zhang Yikai Zhang Xiaoling Hu Mayank Goswami Chao Chen Dimitris N. Metaxas AAML 9 6 0 24 Mar 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 32 13 0 26 Feb 2022
Layer-wise Regularized Adversarial Training using Layers Sustainability Analysis (LSA) framework Mohammad Khalooei M. Homayounpour M. Amirmazlaghani AAML 17 3 0 05 Feb 2022
Benign Overfitting in Adversarially Robust Linear Classification Jinghui Chen Yuan Cao Quanquan Gu AAML SILM 28 10 0 31 Dec 2021
Interpolated Joint Space Adversarial Training for Robust and Generalizable Defenses Chun Pong Lau Jiang-Long Liu Hossein Souri Wei-An Lin S. Feizi Ramalingam Chellappa AAML 27 12 0 12 Dec 2021
Image classifiers can not be made robust to small perturbations Zheng Dai David K Gifford VLM AAML 16 1 0 07 Dec 2021
Trustworthy AI: From Principles to Practices Bo-wen Li Peng Qi Bo Liu Shuai Di Jingen Liu Jiquan Pei Jinfeng Yi Bowen Zhou 117 355 0 04 Oct 2021
Classification and Adversarial examples in an Overparameterized Linear Model: A Signal Processing Perspective Adhyyan Narang Vidya Muthukumar A. Sahai SILM AAML 31 1 0 27 Sep 2021
On the regularized risk of distributionally robust learning over deep neural networks Camilo A. Garcia Trillos Nicolas García Trillos OOD 37 10 0 13 Sep 2021
The mathematics of adversarial attacks in AI -- Why deep learning is unstable despite the existence of stable neural networks Alexander Bastounis A. Hansen Verner Vlacic AAML OOD 24 28 0 13 Sep 2021
Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack Mengting Xu Tao Zhang Zhongnian Li Mingxia Liu Daoqiang Zhang AAML OOD MedIm 25 41 0 05 Mar 2021
Achieving Adversarial Robustness Requires An Active Teacher Chao Ma Lexing Ying 19 1 0 14 Dec 2020
Regularization with Latent Space Virtual Adversarial Training Genki Osada Budrul Ahsan Revoti Prasad Bora Takashi Nishide 24 14 0 26 Nov 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 29 48 0 19 Oct 2020
Multimodal Safety-Critical Scenarios Generation for Decision-Making Algorithms Evaluation Wenhao Ding Baiming Chen Bo-wen Li Kim Ji Eun Ding Zhao AAML 16 98 0 16 Sep 2020
Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks Wei-An Lin Chun Pong Lau Alexander Levine Ramalingam Chellappa S. Feizi AAML 78 60 0 05 Sep 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 25 73 0 07 Aug 2020
Derivation of Information-Theoretically Optimal Adversarial Attacks with Applications to Robust Machine Learning Jirong Yi R. Mudumbai Weiyu Xu AAML 16 2 0 28 Jul 2020
RANDOM MASK: Towards Robust Convolutional Neural Networks Tiange Luo Tianle Cai Mengxiao Zhang Siyu Chen Liwei Wang AAML OOD 11 17 0 27 Jul 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 27 146 0 20 May 2020
Utilizing Network Properties to Detect Erroneous Inputs Matt Gorbett Nathaniel Blanchard AAML 9 6 0 28 Feb 2020
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models Lin Chen Yifei Min Mingrui Zhang Amin Karbasi OOD 27 64 0 11 Feb 2020
Robustness of Bayesian Neural Networks to Gradient-Based Attacks Ginevra Carbone Matthew Wicker Luca Laurenti A. Patané Luca Bortolussi G. Sanguinetti AAML 24 77 0 11 Feb 2020
Understanding the Decision Boundary of Deep Neural Networks: An Empirical Study David Mickisch F. Assion Florens Greßner W. Günther M. Motta AAML 19 34 0 05 Feb 2020
One Man's Trash is Another Man's Treasure: Resisting Adversarial Examples by Adversarial Examples Chang Xiao Changxi Zheng AAML 17 19 0 25 Nov 2019
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey Olakunle Ibitoye Rana Abou-Khamis Mohamed el Shehaby Ashraf Matrawy M. O. Shafiq AAML 26 68 0 06 Nov 2019
Towards Robust and Stable Deep Learning Algorithms for Forward Backward Stochastic Differential Equations Batuhan Güler Alexis Laignelet P. Parpas OOD 18 16 0 25 Oct 2019
Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks Tianyu Pang Kun Xu Jun Zhu AAML 20 103 0 25 Sep 2019
Universal Adversarial Audio Perturbations Sajjad Abdoli L. G. Hafemann Jérôme Rony Ismail Ben Ayed P. Cardinal Alessandro Lameiras Koerich AAML 25 51 0 08 Aug 2019
Adversarially Robust Learning Could Leverage Computational Hardness Sanjam Garg S. Jha Saeed Mahloujifar Mohammad Mahmoody AAML 14 24 0 28 May 2019
Adversarial Training and Robustness for Multiple Perturbations Florian Tramèr Dan Boneh AAML SILM 17 374 0 30 Apr 2019
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples Kevin Roth Yannic Kilcher Thomas Hofmann AAML 21 175 0 13 Feb 2019
Adversarial Examples Are a Natural Consequence of Test Error in Noise Nic Ford Justin Gilmer Nicholas Carlini E. D. Cubuk AAML 22 318 0 29 Jan 2019
Robustness via curvature regularization, and vice versa Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi J. Uesato P. Frossard AAML 10 318 0 23 Nov 2018
Excessive Invariance Causes Adversarial Vulnerability J. Jacobsen Jens Behrmann R. Zemel Matthias Bethge AAML 20 166 0 01 Nov 2018
Certified Adversarial Robustness with Additive Noise Bai Li Changyou Chen Wenlin Wang Lawrence Carin AAML 17 341 0 10 Sep 2018
Adversarial examples from computational constraints Sébastien Bubeck Eric Price Ilya P. Razenshteyn AAML 62 230 0 25 May 2018