Robustness of classifiers: from adversarial to random noise

31 August 2016

Alhussein Fawzi

Seyed-Mohsen Moosavi-Dezfooli

P. Frossard

AAML

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Papers citing "Robustness of classifiers: from adversarial to random noise"

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Title
Quantum Support Vector Regression for Robust Anomaly Detection Kilian Tscharke Maximilian Wendlinger Sebastian Issel Pascal Debus AAML 44 0 0 02 May 2025
Investigating Weight-Perturbed Deep Neural Networks With Application in Iris Presentation Attack Detection Renu Sharma Redwan Sony Arun Ross AAML 21 3 0 21 Nov 2023
HoSNN: Adversarially-Robust Homeostatic Spiking Neural Networks with Adaptive Firing Thresholds Hejia Geng Peng Li AAML 42 3 0 20 Aug 2023
A Theoretical Perspective on Subnetwork Contributions to Adversarial Robustness Jovon Craig Joshua Andle Theodore S. Nowak Salimeh Yasaei Sekeh AAML 53 0 0 07 Jul 2023
Boosting Adversarial Attacks by Leveraging Decision Boundary Information Boheng Zeng LianLi Gao Qilong Zhang Chaoqun Li JingKuan Song Shuaiqi Jing AAML 25 2 0 10 Mar 2023
Uncertainty Injection: A Deep Learning Method for Robust Optimization W. Cui Wei Yu UQCV OOD 27 6 0 23 Feb 2023
AdvCat: Domain-Agnostic Robustness Assessment for Cybersecurity-Critical Applications with Categorical Inputs Helene Orsini Hongyan Bao Yujun Zhou Xiangrui Xu Yufei Han Longyang Yi Wei Wang Xin Gao Xiangliang Zhang AAML 44 1 0 13 Dec 2022
Adversarial Detection by Approximation of Ensemble Boundary T. Windeatt AAML 26 0 0 18 Nov 2022
There is more than one kind of robustness: Fooling Whisper with adversarial examples R. Olivier Bhiksha Raj AAML 40 12 0 26 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
DeltaBound Attack: Efficient decision-based attack in low queries regime L. Rossi AAML 20 0 0 01 Oct 2022
Mixed-Precision Neural Networks: A Survey M. Rakka M. Fouda Pramod P. Khargonekar Fadi J. Kurdahi MQ 27 11 0 11 Aug 2022
Discriminator-Weighted Offline Imitation Learning from Suboptimal Demonstrations Haoran Xu Xianyuan Zhan Honglei Yin Huiling Qin OffRL 26 66 0 20 Jul 2022
Sample Complexity Bounds for Robustly Learning Decision Lists against Evasion Attacks Pascale Gourdeau Varun Kanade Marta Z. Kwiatkowska J. Worrell AAML 21 5 0 12 May 2022
Co-Teaching for Unsupervised Domain Adaptation and Expansion Kaibin Tian Qijie Wei Xirong Li 32 1 0 04 Apr 2022
Stochastic Perturbations of Tabular Features for Non-Deterministic Inference with Automunge Nicholas J. Teague AAML 33 1 0 18 Feb 2022
On Distinctive Properties of Universal Perturbations Sung Min Park K. Wei Kai Y. Xiao Jungshian Li A. Madry AAML 24 2 0 31 Dec 2021
On the Adversarial Robustness of Causal Algorithmic Recourse Ricardo Dominguez-Olmedo Amir-Hossein Karimi Bernhard Schölkopf 46 63 0 21 Dec 2021
Editing a classifier by rewriting its prediction rules Shibani Santurkar Dimitris Tsipras Mahalaxmi Elango David Bau Antonio Torralba A. Madry KELM 186 89 0 02 Dec 2021
Back in Black: A Comparative Evaluation of Recent State-Of-The-Art Black-Box Attacks Kaleel Mahmood Rigel Mahmood Ethan Rathbun Marten van Dijk AAML 19 22 0 29 Sep 2021
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
Evaluating the Robustness of Neural Language Models to Input Perturbations M. Moradi Matthias Samwald AAML 50 96 0 27 Aug 2021
Context-aware Adversarial Training for Name Regularity Bias in Named Entity Recognition Abbas Ghaddar Philippe Langlais Ahmad Rashid Mehdi Rezagholizadeh 39 43 0 24 Jul 2021
Attack Transferability Characterization for Adversarially Robust Multi-label Classification Zhuo Yang Yufei Han Xiangliang Zhang AAML 23 4 0 29 Jun 2021
Bio-inspired Robustness: A Review Harshitha Machiraju Oh-hyeon Choung P. Frossard Michael H. Herzog AAML 37 1 0 16 Mar 2021
A Survey On Universal Adversarial Attack Chaoning Zhang Philipp Benz Chenguo Lin Adil Karjauv Jing Wu In So Kweon AAML 25 90 0 02 Mar 2021
Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification Brendon G. Anderson Ziye Ma Jingqi Li Somayeh Sojoudi 58 1 0 22 Jan 2021
Unlearnable Examples: Making Personal Data Unexploitable Hanxun Huang Xingjun Ma S. Erfani James Bailey Yisen Wang MIACV 156 190 0 13 Jan 2021
Achieving Adversarial Robustness Requires An Active Teacher Chao Ma Lexing Ying 27 1 0 14 Dec 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 36 48 0 19 Oct 2020
Data-Driven Certification of Neural Networks with Random Input Noise Brendon G. Anderson Somayeh Sojoudi AAML 17 11 0 02 Oct 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 29 73 0 07 Aug 2020
Learning from Noisy Labels with Deep Neural Networks: A Survey Hwanjun Song Minseok Kim Dongmin Park Yooju Shin Jae-Gil Lee NoLa 24 964 0 16 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
Arms Race in Adversarial Malware Detection: A Survey Deqiang Li Qianmu Li Yanfang Ye Shouhuai Xu AAML 24 52 0 24 May 2020
Increasing-Margin Adversarial (IMA) Training to Improve Adversarial Robustness of Neural Networks Linhai Ma Liang Liang AAML 26 18 0 19 May 2020
GeoDA: a geometric framework for black-box adversarial attacks A. Rahmati Seyed-Mohsen Moosavi-Dezfooli P. Frossard H. Dai MLAU AAML 31 114 0 13 Mar 2020
Analyzing Accuracy Loss in Randomized Smoothing Defenses Yue Gao Harrison Rosenberg Kassem Fawaz S. Jha Justin Hsu AAML 24 6 0 03 Mar 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
A simple way to make neural networks robust against diverse image corruptions E. Rusak Lukas Schott Roland S. Zimmermann Julian Bitterwolf Oliver Bringmann Matthias Bethge Wieland Brendel 21 64 0 16 Jan 2020
Design of optical neural networks with component imprecisions Michael Y.-S. Fang S. Manipatruni Casimir Wierzynski A. Khosrowshahi M. DeWeese 35 128 0 13 Dec 2019
Loss Aware Post-training Quantization Yury Nahshan Brian Chmiel Chaim Baskin Evgenii Zheltonozhskii Ron Banner A. Bronstein A. Mendelson MQ 37 165 0 17 Nov 2019
Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks Tianyu Pang Kun Xu Jun Zhu AAML 28 103 0 25 Sep 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
Cross-Domain Transferability of Adversarial Perturbations Muzammal Naseer Salman H. Khan M. H. Khan Fahad Shahbaz Khan Fatih Porikli AAML 33 145 0 28 May 2019
Body Shape Privacy in Images: Understanding Privacy and Preventing Automatic Shape Extraction Hosnieh Sattar Katharina Krombholz Gerard Pons-Moll Mario Fritz 3DH 27 3 0 27 May 2019
Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges Rob Ashmore R. Calinescu Colin Paterson AI4TS 27 116 0 10 May 2019
A geometry-inspired decision-based attack Yujia Liu Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 24 51 0 26 Mar 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 22 1,998 0 08 Feb 2019