v1v2 (latest)

Certified Adversarial Robustness via Randomized Smoothing

8 February 2019

Jeremy M. Cohen

Elan Rosenfeld

J. Zico Kolter

AAML

ArXiv (abs)PDF HTML Github (390★)

Papers citing "Certified Adversarial Robustness via Randomized Smoothing"

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Title
AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Metric Learning Hong Wang Yuefan Deng Shinjae Yoo Haibin Ling Yuewei Lin AAML 78 15 0 13 Aug 2021
Meta Gradient Adversarial Attack Zheng Yuan Jie Zhang Yunpei Jia Chuanqi Tan Tao Xue Shiguang Shan AAML 123 79 0 09 Aug 2021
Fairness Properties of Face Recognition and Obfuscation Systems Harrison Rosenberg Brian Tang Kassem Fawaz S. Jha PICV 71 14 0 05 Aug 2021
Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100 Sahil Singla Surbhi Singla Soheil Feizi AAML 101 58 0 05 Aug 2021
Certified Defense via Latent Space Randomized Smoothing with Orthogonal Encoders Huimin Zeng Jiahao Su Furong Huang AAML 57 4 0 01 Aug 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Mian Navid Kardan M. Shah AAML 185 242 0 01 Aug 2021
Model Preserving Compression for Neural Networks Jerry Chee Megan Flynn Anil Damle Chris De Sa 45 10 0 30 Jul 2021
Enhancing Adversarial Robustness via Test-time Transformation Ensembling Juan C. Pérez Motasem Alfarra Guillaume Jeanneret Laura Rueda Ali K. Thabet Guohao Li Pablo Arbelaez 71 26 0 29 Jul 2021
Imbalanced Adversarial Training with Reweighting Wentao Wang Han Xu Xiaorui Liu Yaxin Li B. Thuraisingham Jiliang Tang 92 16 0 28 Jul 2021
On the Certified Robustness for Ensemble Models and Beyond Zhuolin Yang Linyi Li Xiaojun Xu B. Kailkhura Tao Xie Yue Liu AAML 106 50 0 22 Jul 2021
Using Undervolting as an On-Device Defense Against Adversarial Machine Learning Attacks Saikat Majumdar Mohammad Hossein Samavatian Kristin Barber R. Teodorescu AAML 53 7 0 20 Jul 2021
Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions Eike Petersen Yannik Potdevin Esfandiar Mohammadi Stephan Zidowitz Sabrina Breyer ... Sandra Henn Ludwig Pechmann M. Leucker P. Rostalski Christian Herzog FaML AILaw OOD 111 24 0 20 Jul 2021
On the Importance of Regularisation & Auxiliary Information in OOD Detection John Mitros Brian Mac Namee 61 2 0 15 Jul 2021
Trustworthy AI: A Computational Perspective Haochen Liu Yiqi Wang Wenqi Fan Xiaorui Liu Yaxin Li Shaili Jain Yunhao Liu Anil K. Jain Jiliang Tang FaML 205 213 0 12 Jul 2021
ANCER: Anisotropic Certification via Sample-wise Volume Maximization Francisco Eiras Motasem Alfarra M. P. Kumar Philip Torr P. Dokania Guohao Li Adel Bibi 89 32 0 09 Jul 2021
Universal 3-Dimensional Perturbations for Black-Box Attacks on Video Recognition Systems Shangyu Xie Han Wang Yu Kong Yuan Hong AAML 78 27 0 09 Jul 2021
Understanding Intrinsic Robustness Using Label Uncertainty Xiao Zhang David Evans OOD 60 5 0 07 Jul 2021
ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients Alessandro Cappelli Julien Launay Laurent Meunier Ruben Ohana Iacopo Poli AAML 61 4 0 06 Jul 2021
Understanding the Security of Deepfake Detection Xiaoyu Cao Neil Zhenqiang Gong AAML 72 19 0 05 Jul 2021
DeformRS: Certifying Input Deformations with Randomized Smoothing Motasem Alfarra Adel Bibi Naeemullah Khan Philip Torr Guohao Li 76 22 0 02 Jul 2021
Scalable Certified Segmentation via Randomized Smoothing Marc Fischer Maximilian Baader Martin Vechev 78 41 0 01 Jul 2021
Single-Step Adversarial Training for Semantic Segmentation D. Wiens Barbara Hammer SSeg AAML 73 1 0 30 Jun 2021
Local Reweighting for Adversarial Training Ruize Gao Feng Liu Kaiwen Zhou Gang Niu Bo Han James Cheng AAML OOD 32 6 0 30 Jun 2021
The Values Encoded in Machine Learning Research Abeba Birhane Pratyusha Kalluri Dallas Card William Agnew Ravit Dotan Michelle Bao 99 295 0 29 Jun 2021
Evading Adversarial Example Detection Defenses with Orthogonal Projected Gradient Descent Oliver Bryniarski Nabeel Hingun Pedro Pachuca Vincent Wang Nicholas Carlini AAML 84 37 0 28 Jun 2021
Certified Robustness via Randomized Smoothing over Multiplicative Parameters of Input Transformations Nikita Muravev Aleksandr Petiushko AAML 67 8 0 28 Jun 2021
Immuno-mimetic Deep Neural Networks (Immuno-Net) Ren Wang Tianqi Chen Stephen Lindsly Cooper M. Stansbury I. Rajapakse Alfred Hero 38 3 0 27 Jun 2021
Multi-stage Optimization based Adversarial Training Xiaosen Wang Chuanbiao Song Liwei Wang Kun He AAML 33 5 0 26 Jun 2021
Countering Adversarial Examples: Combining Input Transformation and Noisy Training Cheng Zhang Pan Gao AAML 48 3 0 25 Jun 2021
On the (Un-)Avoidability of Adversarial Examples Sadia Chowdhury Ruth Urner AAML 61 1 0 24 Jun 2021
NCIS: Neural Contextual Iterative Smoothing for Purifying Adversarial Perturbations Sungmin Cha Naeun Ko Young Joon Yoo Taesup Moon AAML 73 2 0 22 Jun 2021
Policy Smoothing for Provably Robust Reinforcement Learning Aounon Kumar Alexander Levine Soheil Feizi AAML 131 59 0 21 Jun 2021
Adversarial Training Helps Transfer Learning via Better Representations Zhun Deng Linjun Zhang Kailas Vodrahalli Kenji Kawaguchi James Zou GAN 104 54 0 18 Jun 2021
Adversarial Visual Robustness by Causal Intervention Kaihua Tang Ming Tao Hanwang Zhang CML AAML 85 21 0 17 Jun 2021
CROP: Certifying Robust Policies for Reinforcement Learning through Functional Smoothing Fan Wu Linyi Li Zijian Huang Yevgeniy Vorobeychik Ding Zhao Yue Liu AAML OffRL 85 61 0 17 Jun 2021
Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks Yulong Cao* Ningfei Wang* Chaowei Xiao Dawei Yang Jin Fang Ruigang Yang Qi Alfred Chen Mingyan D. Liu Yue Liu AAML 103 227 0 17 Jun 2021
Towards Adversarial Robustness via Transductive Learning Jiefeng Chen Yang Guo Xi Wu Tianqi Li Qicheng Lao Yingyu Liang S. Jha AAML 55 5 0 15 Jun 2021
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks Chulin Xie Minghao Chen Pin-Yu Chen Yue Liu FedML 108 175 0 15 Jun 2021
How does Heterophily Impact the Robustness of Graph Neural Networks? Theoretical Connections and Practical Implications Jiong Zhu Junchen Jin Donald Loveland Michael T. Schaub Danai Koutra AAML 108 37 0 14 Jun 2021
PopSkipJump: Decision-Based Attack for Probabilistic Classifiers Carl-Johann Simon-Gabriel N. Sheikh Andreas Krause SILM AAML 56 3 0 14 Jun 2021
Boosting Randomized Smoothing with Variance Reduced Classifiers Miklós Z. Horváth Mark Niklas Muller Marc Fischer Martin Vechev AAML UQCV 94 49 0 13 Jun 2021
Inverting Adversarially Robust Networks for Image Synthesis Renan A. Rojas-Gomez Raymond A. Yeh Minh Do A. Nguyen 68 5 0 13 Jun 2021
Adversarial Robustness via Fisher-Rao Regularization Marine Picot Francisco Messina Malik Boudiaf Fabrice Labeau Ismail Ben Ayed Pablo Piantanida AAML 84 25 0 12 Jun 2021
Relaxing Local Robustness Klas Leino Matt Fredrikson AAML 65 8 0 11 Jun 2021
Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks Nezihe Merve Gürel Xiangyu Qi Luka Rimanic Ce Zhang Yue Liu AAML 67 39 0 11 Jun 2021
Adversarial purification with Score-based generative models Jongmin Yoon Sung Ju Hwang Juho Lee DiffM 102 160 0 11 Jun 2021
HASI: Hardware-Accelerated Stochastic Inference, A Defense Against Adversarial Machine Learning Attacks Mohammad Hossein Samavatian Saikat Majumdar Kristin Barber R. Teodorescu AAML 126 4 0 09 Jun 2021
Attacking Adversarial Attacks as A Defense Boxi Wu Heng Pan Li Shen Jindong Gu Shuai Zhao Zhifeng Li Deng Cai Xiaofei He Wei Liu AAML 93 33 0 09 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 103 32 0 09 Jun 2021
Handcrafted Backdoors in Deep Neural Networks Sanghyun Hong Nicholas Carlini Alexey Kurakin 137 76 0 08 Jun 2021