Certified Adversarial Robustness via Randomized Smoothing

8 February 2019

J. Zico Kolter

Papers citing "Certified Adversarial Robustness via Randomized Smoothing"

50 / 548 papers shown

Title
ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients Alessandro Cappelli Julien Launay Laurent Meunier Ruben Ohana Iacopo Poli AAML 29 4 0 06 Jul 2021
Scalable Certified Segmentation via Randomized Smoothing Marc Fischer Maximilian Baader Martin Vechev 43 38 0 01 Jul 2021
The Values Encoded in Machine Learning Research Abeba Birhane Pratyusha Kalluri Dallas Card William Agnew Ravit Dotan Michelle Bao 46 275 0 29 Jun 2021
Certified Robustness via Randomized Smoothing over Multiplicative Parameters of Input Transformations Nikita Muravev Aleksandr Petiushko AAML 26 7 0 28 Jun 2021
Policy Smoothing for Provably Robust Reinforcement Learning Aounon Kumar Alexander Levine Soheil Feizi AAML 27 56 0 21 Jun 2021
Adversarial Training Helps Transfer Learning via Better Representations Zhun Deng Linjun Zhang Kailas Vodrahalli Kenji Kawaguchi James Zou GAN 36 54 0 18 Jun 2021
Adversarial Visual Robustness by Causal Intervention Kaihua Tang Ming Tao Hanwang Zhang CML AAML 37 21 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 40 219 0 17 Jun 2021
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks Chulin Xie Minghao Chen Pin-Yu Chen Yue Liu FedML 41 165 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 37 36 0 14 Jun 2021
Boosting Randomized Smoothing with Variance Reduced Classifiers Miklós Z. Horváth Mark Niklas Muller Marc Fischer Martin Vechev AAML UQCV 26 48 0 13 Jun 2021
Adversarial Robustness via Fisher-Rao Regularization Marine Picot Francisco Messina Malik Boudiaf Fabrice Labeau Ismail Ben Ayed Pablo Piantanida AAML 31 23 0 12 Jun 2021
Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks Nezihe Merve Gürel Xiangyu Qi Luka Rimanic Ce Zhang Yue Liu AAML 27 39 0 11 Jun 2021
Adversarial purification with Score-based generative models Jongmin Yoon Sung Ju Hwang Juho Lee DiffM 37 156 0 11 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 31 32 0 09 Jun 2021
Quantifying and Improving Transferability in Domain Generalization Guojun Zhang Han Zhao Yaoliang Yu Pascal Poupart 53 37 0 07 Jun 2021
A Little Robustness Goes a Long Way: Leveraging Robust Features for Targeted Transfer Attacks Jacob Mitchell Springer Melanie Mitchell Garrett Kenyon AAML 48 43 0 03 Jun 2021
NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels Jingfeng Zhang Xilie Xu Bo Han Tongliang Liu Gang Niu Li-zhen Cui Masashi Sugiyama NoLa AAML 31 9 0 31 May 2021
Practical Convex Formulation of Robust One-hidden-layer Neural Network Training Yatong Bai Tanmay Gautam Yujie Gai Somayeh Sojoudi AAML 38 3 0 25 May 2021
Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks Dequan Wang An Ju Evan Shelhamer David Wagner Trevor Darrell AAML 31 27 0 18 May 2021
Impact of Spatial Frequency Based Constraints on Adversarial Robustness Rémi Bernhard Pierre-Alain Moëllic Martial Mermillod Yannick Bourrier Romain Cohendet M. Solinas M. Reyboz AAML 35 17 0 26 Apr 2021
Random Noise Defense Against Query-Based Black-Box Attacks Zeyu Qin Yanbo Fan H. Zha Baoyuan Wu AAML 34 60 0 23 Apr 2021
Randomized Algorithms for Scientific Computing (RASC) A. Buluç T. Kolda Stefan M. Wild M. Anitescu Anthony Degennaro ... D. Vrabie B. Wohlberg Stephen J. Wright Chao Yang Peter Zwart AI4CE 56 10 0 19 Apr 2021
Rethinking Image-Scaling Attacks: The Interplay Between Vulnerabilities in Machine Learning Systems Yue Gao Ilia Shumailov Kassem Fawaz AAML 65 10 0 18 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 43 65 0 09 Apr 2021
Adversarial Attacks and Defenses for Speech Recognition Systems Piotr Żelasko Sonal Joshi Yiwen Shao Jesus Villalba J. Trmal Najim Dehak Sanjeev Khudanpur AAML 26 28 0 31 Mar 2021
Certifiably-Robust Federated Adversarial Learning via Randomized Smoothing Cheng Chen B. Kailkhura R. Goldhahn Yi Zhou AAML FedML 30 15 0 30 Mar 2021
On the Adversarial Robustness of Vision Transformers Rulin Shao Zhouxing Shi Jinfeng Yi Pin-Yu Chen Cho-Jui Hsieh ViT 40 137 0 29 Mar 2021
Enhancing the Transferability of Adversarial Attacks through Variance Tuning Xiaosen Wang Kun He AAML 52 384 0 29 Mar 2021
Robust Models Are More Interpretable Because Attributions Look Normal Zifan Wang Matt Fredrikson Anupam Datta OOD FAtt 40 25 0 20 Mar 2021
Boosting Adversarial Transferability through Enhanced Momentum Xiaosen Wang Jiadong Lin Han Hu Jingdong Wang Kun He AAML 21 76 0 19 Mar 2021
Adversarial Training is Not Ready for Robot Learning Mathias Lechner Ramin Hasani Radu Grosu Daniela Rus T. Henzinger AAML 43 34 0 15 Mar 2021
A Unified Game-Theoretic Interpretation of Adversarial Robustness Jie Ren Die Zhang Yisen Wang Lu Chen Zhanpeng Zhou ... Xu Cheng Xin Eric Wang Meng Zhou Jie Shi Quanshi Zhang AAML 72 22 0 12 Mar 2021
Consistency Regularization for Adversarial Robustness Jihoon Tack Sihyun Yu Jongheon Jeong Minseon Kim Sung Ju Hwang Jinwoo Shin AAML 41 58 0 08 Mar 2021
PRIMA: General and Precise Neural Network Certification via Scalable Convex Hull Approximations Mark Niklas Muller Gleb Makarchuk Gagandeep Singh Markus Püschel Martin Vechev 46 91 0 05 Mar 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 43 41 0 05 Mar 2021
A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness Jacob D. Abernethy Pranjal Awasthi Satyen Kale AAML 32 6 0 01 Mar 2021
Adversarial Robustness with Non-uniform Perturbations Ece Naz Erdemir Jeffrey Bickford Luca Melis Sergul Aydore AAML 29 26 0 24 Feb 2021
Globally-Robust Neural Networks Klas Leino Zifan Wang Matt Fredrikson AAML OOD 85 126 0 16 Feb 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training Vasu Singla Sahil Singla David Jacobs Soheil Feizi AAML 43 45 0 15 Feb 2021
Connecting Interpretability and Robustness in Decision Trees through Separation Michal Moshkovitz Yao-Yuan Yang Kamalika Chaudhuri 35 22 0 14 Feb 2021
Mixed Nash Equilibria in the Adversarial Examples Game Laurent Meunier M. Scetbon Rafael Pinot Jamal Atif Y. Chevaleyre AAML 42 29 0 13 Feb 2021
On the Paradox of Certified Training Nikola Jovanović Mislav Balunović Maximilian Baader Martin Vechev OOD 33 13 0 12 Feb 2021
Efficient Certified Defenses Against Patch Attacks on Image Classifiers J. H. Metzen Maksym Yatsura AAML 31 40 0 08 Feb 2021
Adversarial Training Makes Weight Loss Landscape Sharper in Logistic Regression Masanori Yamada Sekitoshi Kanai Tomoharu Iwata Tomokatsu Takahashi Yuki Yamanaka Hiroshi Takahashi Atsutoshi Kumagai AAML 35 9 0 05 Feb 2021
Robust Adversarial Attacks Against DNN-Based Wireless Communication Systems Alireza Bahramali Milad Nasr Amir Houmansadr Dennis Goeckel Don Towsley AAML 45 54 0 01 Feb 2021
Admix: Enhancing the Transferability of Adversarial Attacks Xiaosen Wang Xu He Jingdong Wang Kun He AAML 86 195 0 31 Jan 2021
Differentiable sampling of molecular geometries with uncertainty-based adversarial attacks Daniel Schwalbe-Koda Aik Rui Tan Rafael Gómez-Bombarelli AAML 33 60 0 27 Jan 2021
Adversarial Machine Learning in Text Analysis and Generation I. Alsmadi AAML 32 5 0 14 Jan 2021
Adversarial Robustness by Design through Analog Computing and Synthetic Gradients Alessandro Cappelli Ruben Ohana Julien Launay Laurent Meunier Iacopo Poli Florent Krzakala AAML 72 13 0 06 Jan 2021