Certified Defenses against Adversarial Examples

29 January 2018

Papers citing "Certified Defenses against Adversarial Examples"

50 / 250 papers shown

Title
Double Sampling Randomized Smoothing Linyi Li Jiawei Zhang Tao Xie Bo-wen Li AAML 17 23 0 16 Jun 2022
Can pruning improve certified robustness of neural networks? Zhangheng Li Tianlong Chen Linyi Li Bo-wen Li Zhangyang Wang AAML 13 11 0 15 Jun 2022
Building Robust Ensembles via Margin Boosting Dinghuai Zhang Hongyang R. Zhang Aaron Courville Yoshua Bengio Pradeep Ravikumar A. Suggala AAML UQCV 48 15 0 07 Jun 2022
Towards Evading the Limits of Randomized Smoothing: A Theoretical Analysis Raphael Ettedgui Alexandre Araujo Rafael Pinot Y. Chevaleyre Jamal Atif AAML 34 3 0 03 Jun 2022
FETA: Fairness Enforced Verifying, Training, and Predicting Algorithms for Neural Networks Kiarash Mohammadi Aishwarya Sivaraman G. Farnadi 25 5 0 01 Jun 2022
(De-)Randomized Smoothing for Decision Stump Ensembles Miklós Z. Horváth Mark Niklas Muller Marc Fischer Martin Vechev 30 3 0 27 May 2022
Smooth-Reduce: Leveraging Patches for Improved Certified Robustness Ameya Joshi Minh Pham Minsu Cho Leonid Boytsov Filipe Condessa J. Zico Kolter C. Hegde UQCV AAML 32 2 0 12 May 2022
Do You Think You Can Hold Me? The Real Challenge of Problem-Space Evasion Attacks Harel Berger A. Dvir Chen Hajaj Rony Ronen AAML 29 3 0 09 May 2022
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective Yimeng Zhang Yuguang Yao Jinghan Jia Jinfeng Yi Min-Fong Hong Shiyu Chang Sijia Liu AAML 26 33 0 27 Mar 2022
Defending Black-box Skeleton-based Human Activity Classifiers He Wang Yunfeng Diao Zichang Tan G. Guo AAML 51 10 0 09 Mar 2022
A Quantitative Geometric Approach to Neural-Network Smoothness Zehao Wang Gautam Prakriya S. Jha 43 13 0 02 Mar 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 32 13 0 26 Feb 2022
Robust Probabilistic Time Series Forecasting Taeho Yoon Youngsuk Park Ernest K. Ryu Yuyang Wang AAML AI4TS 20 18 0 24 Feb 2022
Layer-wise Regularized Adversarial Training using Layers Sustainability Analysis (LSA) framework Mohammad Khalooei M. Homayounpour M. Amirmazlaghani AAML 25 3 0 05 Feb 2022
LyaNet: A Lyapunov Framework for Training Neural ODEs I. D. Rodriguez Aaron D. Ames Yisong Yue 33 51 0 05 Feb 2022
Robust Binary Models by Pruning Randomly-initialized Networks Chen Liu Ziqi Zhao Sabine Süsstrunk Mathieu Salzmann TPM AAML MQ 32 4 0 03 Feb 2022
Smoothed Embeddings for Certified Few-Shot Learning Mikhail Aleksandrovich Pautov Olesya Kuznetsova Nurislam Tursynbek Aleksandr Petiushko Ivan Oseledets 42 5 0 02 Feb 2022
Constrained Gradient Descent: A Powerful and Principled Evasion Attack Against Neural Networks Weiran Lin Keane Lucas Lujo Bauer Michael K. Reiter Mahmood Sharif AAML 31 5 0 28 Dec 2021
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training Chen Liu Zhichao Huang Mathieu Salzmann Tong Zhang Sabine Süsstrunk AAML 23 13 0 14 Dec 2021
Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting Junhua Zou Zhisong Pan Junyang Qiu Xin Liu Ting Rui Wei Li 15 67 0 11 Dec 2021
The Fundamental Limits of Interval Arithmetic for Neural Networks M. Mirman Maximilian Baader Martin Vechev 32 6 0 09 Dec 2021
Mutual Adversarial Training: Learning together is better than going alone Jiang-Long Liu Chun Pong Lau Hossein Souri S. Feizi Ramalingam Chellappa OOD AAML 43 24 0 09 Dec 2021
Certified Adversarial Defenses Meet Out-of-Distribution Corruptions: Benchmarking Robustness and Simple Baselines Jiachen Sun Akshay Mehra B. Kailkhura Pin-Yu Chen Dan Hendrycks Jihun Hamm Z. Morley Mao AAML 35 21 0 01 Dec 2021
Is the Rush to Machine Learning Jeopardizing Safety? Results of a Survey M. Askarpour Alan Wassyng M. Lawford R. Paige Z. Diskin 25 0 0 29 Nov 2021
Adaptive Perturbation for Adversarial Attack Zheng Yuan Jie Zhang Zhaoyan Jiang Liangliang Li Shiguang Shan AAML 27 3 0 27 Nov 2021
Reachability analysis of neural networks using mixed monotonicity Pierre-Jean Meyer 54 8 0 15 Nov 2021
TESDA: Transform Enabled Statistical Detection of Attacks in Deep Neural Networks C. Amarnath Aishwarya H. Balwani Kwondo Ma Abhijit Chatterjee AAML 18 3 0 16 Oct 2021
Trustworthy AI: From Principles to Practices Bo-wen Li Peng Qi Bo Liu Shuai Di Jingen Liu Jiquan Pei Jinfeng Yi Bowen Zhou 119 356 0 04 Oct 2021
Neural Network Verification in Control M. Everett AAML 34 16 0 30 Sep 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 38 16 0 20 Sep 2021
Improving the Robustness of Adversarial Attacks Using an Affine-Invariant Gradient Estimator Wenzhao Xiang Hang Su Chang-rui Liu Yandong Guo Shibao Zheng AAML 29 5 0 13 Sep 2021
Impact of Attention on Adversarial Robustness of Image Classification Models Prachi Agrawal Narinder Singh Punn S. K. Sonbhadra Sonali Agarwal AAML 24 6 0 02 Sep 2021
Learning to Give Checkable Answers with Prover-Verifier Games Cem Anil Guodong Zhang Yuhuai Wu Roger C. Grosse 24 15 0 27 Aug 2021
A Hierarchical Assessment of Adversarial Severity Guillaume Jeanneret Juan Pérez Pablo Arbeláez AAML 30 2 0 26 Aug 2021
PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier Chong Xiang Saeed Mahloujifar Prateek Mittal VLM AAML 24 73 0 20 Aug 2021
Meta Gradient Adversarial Attack Zheng Yuan Jie Zhang Yunpei Jia Chuanqi Tan Tao Xue Shiguang Shan AAML 49 78 0 09 Aug 2021
Reachability Analysis of Neural Feedback Loops M. Everett Golnaz Habibi Chuangchuang Sun Jonathan P. How 19 53 0 09 Aug 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Mian Navid Kardan M. Shah AAML 31 236 0 01 Aug 2021
Imbalanced Adversarial Training with Reweighting Wentao Wang Han Xu Xiaorui Liu Yaxin Li B. Thuraisingham Jiliang Tang 37 16 0 28 Jul 2021
Neural Network Branch-and-Bound for Neural Network Verification Florian Jaeckle Jingyue Lu M. P. Kumar 18 8 0 27 Jul 2021
Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them Florian Tramèr AAML 30 65 0 24 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 104 196 0 12 Jul 2021
Scalable Certified Segmentation via Randomized Smoothing Marc Fischer Maximilian Baader Martin Vechev 18 38 0 01 Jul 2021
Adversarial Training Helps Transfer Learning via Better Representations Zhun Deng Linjun Zhang Kailas Vodrahalli Kenji Kawaguchi James Zou GAN 36 52 0 18 Jun 2021
Localized Uncertainty Attacks Ousmane Amadou Dia Theofanis Karaletsos C. Hazirbas Cristian Canton Ferrer I. Kabul E. Meijer AAML 24 2 0 17 Jun 2021
Adversarial Robustness via Fisher-Rao Regularization Marine Picot Francisco Messina Malik Boudiaf Fabrice Labeau Ismail Ben Ayed Pablo Piantanida AAML 28 23 0 12 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 21 31 0 09 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
A BIC-based Mixture Model Defense against Data Poisoning Attacks on Classifiers Xi Li David J. Miller Zhen Xiang G. Kesidis AAML 16 0 0 28 May 2021
DNNV: A Framework for Deep Neural Network Verification David Shriver Sebastian G. Elbaum Matthew B. Dwyer 21 31 0 26 May 2021