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Certified Robustness to Adversarial Examples with Differential Privacy

9 February 2018

Papers citing "Certified Robustness to Adversarial Examples with Differential Privacy"

50 / 567 papers shown

Title
Natural Language Understanding with Privacy-Preserving BERT Chen Qu Weize Kong Liu Yang Mingyang Zhang Michael Bendersky Marc Najork 103 76 0 15 Apr 2021
Simpler Certified Radius Maximization by Propagating Covariances Xingjian Zhen Rudrasis Chakraborty Vikas Singh AAML 40 5 0 13 Apr 2021
Practical Defences Against Model Inversion Attacks for Split Neural Networks Tom Titcombe A. Hall Pavlos Papadopoulos Daniele Romanini FedML 68 58 0 12 Apr 2021
Fast Certified Robust Training with Short Warmup Zhouxing Shi Yihan Wang Huan Zhang Jinfeng Yi Cho-Jui Hsieh AAML 99 57 0 31 Mar 2021
Robustness Certification for Point Cloud Models Tobias Lorenz Anian Ruoss Mislav Balunović Gagandeep Singh Martin Vechev 3DPC 101 26 0 30 Mar 2021
Certifiably-Robust Federated Adversarial Learning via Randomized Smoothing Cheng Chen B. Kailkhura R. Goldhahn Yi Zhou AAML FedML 64 16 0 30 Mar 2021
Understanding Generalization in Adversarial Training via the Bias-Variance Decomposition Yaodong Yu Zitong Yang Yan Sun Jacob Steinhardt Yi-An Ma 64 17 0 17 Mar 2021
Improved, Deterministic Smoothing for L_1 Certified Robustness Alexander Levine Soheil Feizi AAML 99 47 0 17 Mar 2021
Constant Random Perturbations Provide Adversarial Robustness with Minimal Effect on Accuracy Bronya R. Chernyak Bhiksha Raj Tamir Hazan Joseph Keshet AAML 65 1 0 15 Mar 2021
Adversarial Training is Not Ready for Robot Learning Mathias Lechner Ramin Hasani Radu Grosu Daniela Rus T. Henzinger AAML 100 34 0 15 Mar 2021
Membership Inference Attacks on Machine Learning: A Survey Hongsheng Hu Z. Salcic Lichao Sun Gillian Dobbie Philip S. Yu Xuyun Zhang MIACV 125 448 0 14 Mar 2021
DP-Image: Differential Privacy for Image Data in Feature Space Hanyu Xue Bo Liu Ming Ding Tianqing Zhu Dayong Ye Li Song Wanlei Zhou 89 36 0 12 Mar 2021
Stochastic-HMDs: Adversarial Resilient Hardware Malware Detectors through Voltage Over-scaling Md. Shohidul Islam Ihsen Alouani Khaled N. Khasawneh AAML 41 1 0 11 Mar 2021
Revisiting Model's Uncertainty and Confidences for Adversarial Example Detection Ahmed Aldahdooh W. Hamidouche Olivier Déforges AAML 155 29 0 09 Mar 2021
Insta-RS: Instance-wise Randomized Smoothing for Improved Robustness and Accuracy Chong Chen Kezhi Kong Peihong Yu J. Luque Tom Goldstein Furong Huang AAML 64 8 0 07 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 95 93 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 105 45 0 05 Mar 2021
PointGuard: Provably Robust 3D Point Cloud Classification Hongbin Liu Jinyuan Jia Neil Zhenqiang Gong 3DPC 123 75 0 04 Mar 2021
A Modified Drake Equation for Assessing Adversarial Risk to Machine Learning Models Josh Kalin David Noever Matthew Ciolino AAML 387 1 0 03 Mar 2021
A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness Jacob D. Abernethy Pranjal Awasthi Satyen Kale AAML 59 6 0 01 Mar 2021
On the robustness of randomized classifiers to adversarial examples Rafael Pinot Laurent Meunier Florian Yger Cédric Gouy-Pailler Y. Chevaleyre Jamal Atif AAML 75 14 0 22 Feb 2021
Center Smoothing: Certified Robustness for Networks with Structured Outputs Aounon Kumar Tom Goldstein OOD AAML UQCV 84 19 0 19 Feb 2021
Globally-Robust Neural Networks Klas Leino Zifan Wang Matt Fredrikson AAML OOD 162 131 0 16 Feb 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training Vasu Singla Sahil Singla David Jacobs Soheil Feizi AAML 102 47 0 15 Feb 2021
Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons Bohang Zhang Tianle Cai Zhou Lu Di He Liwei Wang OOD 92 51 0 10 Feb 2021
Towards Bridging the gap between Empirical and Certified Robustness against Adversarial Examples Jay Nandy Sudipan Saha Wynne Hsu Mong Li Lee Xiaosu Zhu AAML 82 4 0 09 Feb 2021
Security and Privacy for Artificial Intelligence: Opportunities and Challenges Ayodeji Oseni Nour Moustafa Helge Janicke Peng Liu Z. Tari A. Vasilakos AAML 67 52 0 09 Feb 2021
Efficient Certified Defenses Against Patch Attacks on Image Classifiers J. H. Metzen Maksym Yatsura AAML 61 41 0 08 Feb 2021
DetectorGuard: Provably Securing Object Detectors against Localized Patch Hiding Attacks Chong Xiang Prateek Mittal AAML 113 53 0 05 Feb 2021
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models Yugeng Liu Rui Wen Xinlei He A. Salem Zhikun Zhang Michael Backes Emiliano De Cristofaro Mario Fritz Yang Zhang AAML 106 133 0 04 Feb 2021
Adversarially Robust Learning with Unknown Perturbation Sets Omar Montasser Steve Hanneke Nathan Srebro AAML 85 28 0 03 Feb 2021
Understanding and Achieving Efficient Robustness with Adversarial Supervised Contrastive Learning Anh-Vu Bui Trung Le He Zhao Paul Montague S. Çamtepe Dinh Q. Phung AAML 53 14 0 25 Jan 2021
DiPSeN: Differentially Private Self-normalizing Neural Networks For Adversarial Robustness in Federated Learning Olakunle Ibitoye M. O. Shafiq Ashraf Matrawy FedML 55 19 0 08 Jan 2021
Towards a Robust and Trustworthy Machine Learning System Development: An Engineering Perspective Pulei Xiong Scott Buffett Shahrear Iqbal Philippe Lamontagne M. Mamun Heather Molyneaux OOD 81 15 0 08 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 131 13 0 06 Jan 2021
Advances in Electron Microscopy with Deep Learning Jeffrey M. Ede 107 3 0 04 Jan 2021
Robustness, Privacy, and Generalization of Adversarial Training Fengxiang He Shaopeng Fu Bohan Wang Dacheng Tao 125 10 0 25 Dec 2020
Adversarial Momentum-Contrastive Pre-Training Cong Xu Dan Li Min Yang SSL 74 15 0 24 Dec 2020
AWA: Adversarial Website Adaptation A. M. Sadeghzadeh Behrad Tajali R. Jalili AAML 69 20 0 20 Dec 2020
Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses Micah Goldblum Dimitris Tsipras Chulin Xie Xinyun Chen Avi Schwarzschild Basel Alomair Aleksander Madry Yue Liu Tom Goldstein SILM 144 283 0 18 Dec 2020
Robustness Threats of Differential Privacy Nurislam Tursynbek Aleksandr Petiushko Ivan Oseledets AAML 97 14 0 14 Dec 2020
Attack Agnostic Detection of Adversarial Examples via Random Subspace Analysis Nathan G. Drenkow Neil Fendley Philippe Burlina AAML 70 2 0 11 Dec 2020
DSRNA: Differentiable Search of Robust Neural Architectures Ramtin Hosseini Xingyi Yang P. Xie OOD AAML 63 53 0 11 Dec 2020
Data-Dependent Randomized Smoothing Motasem Alfarra Adel Bibi Philip Torr Guohao Li UQCV 110 35 0 08 Dec 2020
Learning to Separate Clusters of Adversarial Representations for Robust Adversarial Detection Byunggill Joe Jihun Hamm Sung Ju Hwang Sooel Son I. Shin AAML OOD 57 0 0 07 Dec 2020
Advocating for Multiple Defense Strategies against Adversarial Examples Alexandre Araujo Laurent Meunier Rafael Pinot Benjamin Négrevergne AAML 38 9 0 04 Dec 2020
How Robust are Randomized Smoothing based Defenses to Data Poisoning? Akshay Mehra B. Kailkhura Pin-Yu Chen Jihun Hamm OOD AAML 113 32 0 02 Dec 2020
Adversarial Robustness Across Representation Spaces Pranjal Awasthi George Yu Chun-Sung Ferng Andrew Tomkins Da-Cheng Juan OOD AAML 83 11 0 01 Dec 2020
Robust and Private Learning of Halfspaces Badih Ghazi Ravi Kumar Pasin Manurangsi Thao Nguyen 86 12 0 30 Nov 2020
Deterministic Certification to Adversarial Attacks via Bernstein Polynomial Approximation Ching-Chia Kao Jhe-Bang Ko Chun-Shien Lu AAML 55 1 0 28 Nov 2020