Are adversarial examples inevitable?

6 September 2018

Papers citing "Are adversarial examples inevitable?"

50 / 68 papers shown

Title
Robustness Analysis against Adversarial Patch Attacks in Fully Unmanned Stores Hyunsik Na Wonho Lee Seungdeok Roh Sohee Park Daeseon Choi AAML 23 0 0 13 May 2025
Adversarial ML Problems Are Getting Harder to Solve and to Evaluate Javier Rando Jie Zhang Nicholas Carlini F. Tramèr AAML ELM 65 3 0 04 Feb 2025
On The Relationship Between Universal Adversarial Attacks And Sparse Representations Dana Weitzner Raja Giryes AAML 32 0 0 14 Nov 2023
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness Ambar Pal Huaijin Hao Rene Vidal 26 8 0 28 Sep 2023
The Boundaries of Verifiable Accuracy, Robustness, and Generalisation in Deep Learning Alexander Bastounis Alexander N. Gorban Anders C. Hansen D. Higham Danil Prokhorov Oliver J. Sutton I. Tyukin Qinghua Zhou OOD 18 4 0 13 Sep 2023
Can We Rely on AI? D. Higham AAML 43 0 0 29 Aug 2023
Robust Linear Regression: Phase-Transitions and Precise Tradeoffs for General Norms Elvis Dohmatob M. Scetbon AAML OOD 28 0 0 01 Aug 2023
Eigenpatches -- Adversarial Patches from Principal Components Jens Bayer S. Becker David Munch Michael Arens AAML 38 1 0 19 Jun 2023
Exploiting Frequency Spectrum of Adversarial Images for General Robustness Chun Yang Tan K. Kawamoto Hiroshi Kera AAML OOD 34 1 0 15 May 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
Demystifying Causal Features on Adversarial Examples and Causal Inoculation for Robust Network by Adversarial Instrumental Variable Regression Junho Kim Byung-Kwan Lee Yonghyun Ro CML AAML 28 18 0 02 Mar 2023
Adversarial Detection by Approximation of Ensemble Boundary T. Windeatt AAML 26 0 0 18 Nov 2022
Evolution of Neural Tangent Kernels under Benign and Adversarial Training Noel Loo Ramin Hasani Alexander Amini Daniela Rus AAML 36 13 0 21 Oct 2022
When are Local Queries Useful for Robust Learning? Pascale Gourdeau Varun Kanade Marta Z. Kwiatkowska J. Worrell OOD 40 1 0 12 Oct 2022
Sound and Complete Verification of Polynomial Networks Elias Abad Rocamora Mehmet Fatih Şahin Fanghui Liu Grigorios G. Chrysos V. Cevher 23 5 0 15 Sep 2022
Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power Binghui Li Jikai Jin Han Zhong J. Hopcroft Liwei Wang OOD 82 27 0 27 May 2022
Sample Complexity Bounds for Robustly Learning Decision Lists against Evasion Attacks Pascale Gourdeau Varun Kanade Marta Z. Kwiatkowska J. Worrell AAML 18 5 0 12 May 2022
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes Elvis Dohmatob A. Bietti AAML 39 13 0 22 Mar 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 34 13 0 26 Feb 2022
Classification and Adversarial examples in an Overparameterized Linear Model: A Signal Processing Perspective Adhyyan Narang Vidya Muthukumar A. Sahai SILM AAML 36 1 0 27 Sep 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 40 16 0 20 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 32 28 0 13 Sep 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Mian Navid Kardan M. Shah AAML 36 236 0 01 Aug 2021
The Feasibility and Inevitability of Stealth Attacks I. Tyukin D. Higham Alexander Bastounis Eliyas Woldegeorgis Alexander N. Gorban AAML 22 19 0 26 Jun 2021
A Little Robustness Goes a Long Way: Leveraging Robust Features for Targeted Transfer Attacks Jacob Mitchell Springer Melanie Mitchell Garrett Kenyon AAML 31 43 0 03 Jun 2021
Who's Afraid of Adversarial Transferability? Ziv Katzir Yuval Elovici SILM AAML 27 9 0 02 May 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 33 41 0 05 Mar 2021
A Survey On Universal Adversarial Attack Chaoning Zhang Philipp Benz Chenguo Lin Adil Karjauv Jing Wu In So Kweon AAML 23 90 0 02 Mar 2021
Do Input Gradients Highlight Discriminative Features? Harshay Shah Prateek Jain Praneeth Netrapalli AAML FAtt 28 57 0 25 Feb 2021
"What's in the box?!": Deflecting Adversarial Attacks by Randomly Deploying Adversarially-Disjoint Models Sahar Abdelnabi Mario Fritz AAML 27 7 0 09 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
Achieving Adversarial Robustness Requires An Active Teacher Chao Ma Lexing Ying 27 1 0 14 Dec 2020
Adversarial Classification: Necessary conditions and geometric flows Nicolas García Trillos Ryan W. Murray AAML 37 19 0 21 Nov 2020
Adversarial Robust Training of Deep Learning MRI Reconstruction Models Francesco Calivá Kaiyang Cheng Rutwik Shah V. Pedoia OOD AAML MedIm 30 10 0 30 Oct 2020
GreedyFool: Multi-Factor Imperceptibility and Its Application to Designing a Black-box Adversarial Attack Hui Liu Bo Zhao Minzhi Ji Peng Liu AAML 29 6 0 14 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 16 100 0 16 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
RANDOM MASK: Towards Robust Convolutional Neural Networks Tiange Luo Tianle Cai Mengxiao Zhang Siyu Chen Liwei Wang AAML OOD 19 17 0 27 Jul 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
Provable tradeoffs in adversarially robust classification Yan Sun Hamed Hassani David Hong Alexander Robey 23 53 0 09 Jun 2020
Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers S. Melacci Gabriele Ciravegna Angelo Sotgiu Ambra Demontis Battista Biggio Marco Gori Fabio Roli 19 14 0 06 Jun 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 39 147 0 20 May 2020
Certifying Joint Adversarial Robustness for Model Ensembles M. Jonas David Evans AAML 21 2 0 21 Apr 2020
Anomalous Example Detection in Deep Learning: A Survey Saikiran Bulusu B. Kailkhura Bo-wen Li P. Varshney D. Song AAML 28 47 0 16 Mar 2020
Gödel's Sentence Is An Adversarial Example But Unsolvable Xiaodong Qi Lansheng Han AAML 30 0 0 25 Feb 2020
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models Lin Chen Yifei Min Mingrui Zhang Amin Karbasi OOD 38 64 0 11 Feb 2020
Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness Aounon Kumar Alexander Levine Tom Goldstein S. Feizi 15 94 0 08 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
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples Nils Lukas Yuxuan Zhang Florian Kerschbaum MLAU FedML AAML 39 144 0 02 Dec 2019
Playing it Safe: Adversarial Robustness with an Abstain Option Cassidy Laidlaw S. Feizi AAML 31 20 0 25 Nov 2019