Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality

8 January 2018

Papers citing "Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality"

50 / 157 papers shown

Title
A Mask-Based Adversarial Defense Scheme Weizhen Xu Chenyi Zhang Fangzhen Zhao Liangda Fang AAML 30 3 0 21 Apr 2022
Topology and geometry of data manifold in deep learning German Magai A. Ayzenberg AAML 21 11 0 19 Apr 2022
Adversarial Neon Beam: A Light-based Physical Attack to DNNs Chen-Hao Hu Weiwen Shi Wen Li AAML 43 8 0 02 Apr 2022
Enhancing Adversarial Training with Second-Order Statistics of Weights Gao Jin Xinping Yi Wei Huang S. Schewe Xiaowei Huang AAML 29 47 0 11 Mar 2022
Poisoning Attacks and Defenses on Artificial Intelligence: A Survey M. A. Ramírez Song-Kyoo Kim H. A. Hamadi Ernesto Damiani Young-Ji Byon Tae-Yeon Kim C. Cho C. Yeun AAML 25 37 0 21 Feb 2022
Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization Xiaojun Xu Jacky Y. Zhang Evelyn Ma Danny Son Oluwasanmi Koyejo Bo-wen Li 20 10 0 03 Feb 2022
A Stochastic Bundle Method for Interpolating Networks Alasdair Paren Leonard Berrada Rudra P. K. Poudel M. P. Kumar 24 4 0 29 Jan 2022
Adversarially Robust Classification by Conditional Generative Model Inversion Mitra Alirezaei Tolga Tasdizen AAML 14 0 0 12 Jan 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 Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 212 345 0 15 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
Adv-4-Adv: Thwarting Changing Adversarial Perturbations via Adversarial Domain Adaptation Tianyue Zheng Zhe Chen Shuya Ding Chao Cai Jun Luo AAML 35 5 0 01 Dec 2021
Medical Aegis: Robust adversarial protectors for medical images Qingsong Yao Zecheng He S. Kevin Zhou AAML MedIm 30 2 0 22 Nov 2021
Detecting AutoAttack Perturbations in the Frequency Domain P. Lorenz P. Harder Dominik Strassel M. Keuper J. Keuper AAML 19 13 0 16 Nov 2021
Robust and Accurate Object Detection via Self-Knowledge Distillation Weipeng Xu Pengzhi Chu Renhao Xie Xiongziyan Xiao Hongcheng Huang AAML ObjD 27 4 0 14 Nov 2021
ε-weakened Robustness of Deep Neural Networks Pei Huang Yuting Yang Minghao Liu Fuqi Jia Feifei Ma Jian Zhang AAML 27 18 0 29 Oct 2021
Channel redundancy and overlap in convolutional neural networks with channel-wise NNK graphs David Bonet Antonio Ortega Javier Ruiz-Hidalgo Sarath Shekkizhar GNN 33 7 0 18 Oct 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Hanxun Huang Yisen Wang S. Erfani Quanquan Gu James Bailey Xingjun Ma AAML TPM 46 100 0 07 Oct 2021
Improving Adversarial Robustness for Free with Snapshot Ensemble Yihao Wang AAML UQCV 17 1 0 07 Oct 2021
A Uniform Framework for Anomaly Detection in Deep Neural Networks Fangzhen Zhao Chenyi Zhang Naipeng Dong Zefeng You Zhenxin Wu AAML OOD OODD 30 9 0 06 Oct 2021
Local Intrinsic Dimensionality Signals Adversarial Perturbations Sandamal Weerasinghe T. Alpcan S. Erfani C. Leckie Benjamin I. P. Rubinstein AAML 23 0 0 24 Sep 2021
Modeling Adversarial Noise for Adversarial Training Dawei Zhou Nannan Wang Bo Han Tongliang Liu AAML 38 15 0 21 Sep 2021
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest Gilad Cohen Raja Giryes AAML 40 4 0 16 Sep 2021
TREATED:Towards Universal Defense against Textual Adversarial Attacks Bin Zhu Zhaoquan Gu Le Wang Zhihong Tian AAML 36 8 0 13 Sep 2021
Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them Florian Tramèr AAML 30 65 0 24 Jul 2021
On the Certified Robustness for Ensemble Models and Beyond Zhuolin Yang Linyi Li Xiaojun Xu B. Kailkhura Tao Xie Bo-wen Li AAML 29 48 0 22 Jul 2021
Unsupervised Detection of Adversarial Examples with Model Explanations Gihyuk Ko Gyumin Lim AAML GAN 33 5 0 22 Jul 2021
Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot Classification Dong Lee Sae-Young Chung 29 20 0 22 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
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 23 9 0 31 May 2021
Sparta: Spatially Attentive and Adversarially Robust Activation Qing Guo Felix Juefei Xu Changqing Zhou Wei Feng Yang Liu Song Wang AAML 33 4 0 18 May 2021
BAARD: Blocking Adversarial Examples by Testing for Applicability, Reliability and Decidability Luke Chang Katharina Dost Kaiqi Zhao Ambra Demontis Fabio Roli Gillian Dobbie Jörg Simon Wicker AAML 27 2 0 02 May 2021
Removing Adversarial Noise in Class Activation Feature Space Dawei Zhou N. Wang Chunlei Peng Xinbo Gao Xiaoyu Wang Jun Yu Tongliang Liu AAML 30 28 0 19 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 36 65 0 09 Apr 2021
LiBRe: A Practical Bayesian Approach to Adversarial Detection Zhijie Deng Xiao Yang Shizhen Xu Hang Su Jun Zhu BDL AAML 20 61 0 27 Mar 2021
A Unified Game-Theoretic Interpretation of Adversarial Robustness Jie Ren Die Zhang Yisen Wang Lu Chen Zhanpeng Zhou ... Xu Cheng Xin 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 57 0 08 Mar 2021
SpectralDefense: Detecting Adversarial Attacks on CNNs in the Fourier Domain P. Harder Franz-Josef Pfreundt M. Keuper J. Keuper AAML 27 48 0 04 Mar 2021
Understanding Robustness in Teacher-Student Setting: A New Perspective Zhuolin Yang Zhaoxi Chen Tiffany Cai Xinyun Chen Bo-wen Li Yuandong Tian AAML 35 2 0 25 Feb 2021
Unlearnable Examples: Making Personal Data Unexploitable Hanxun Huang Xingjun Ma S. Erfani James Bailey Yisen Wang MIACV 156 190 0 13 Jan 2021
A Deep Marginal-Contrastive Defense against Adversarial Attacks on 1D Models Mohammed Hassanin Nour Moustafa M. Tahtali AAML 24 2 0 08 Dec 2020
Feature Space Singularity for Out-of-Distribution Detection Haiwen Huang Zhihan Li Lulu Wang Sishuo Chen Bin Dong Xinyu Zhou OODD 22 65 0 30 Nov 2020
A Sweet Rabbit Hole by DARCY: Using Honeypots to Detect Universal Trigger's Adversarial Attacks Thai Le Noseong Park Dongwon Lee 10 23 0 20 Nov 2020
Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations Jinyuan Jia Binghui Wang Xiaoyu Cao Hongbin Liu Neil Zhenqiang Gong 16 24 0 15 Nov 2020
The Vulnerability of the Neural Networks Against Adversarial Examples in Deep Learning Algorithms Rui Zhao AAML 34 1 0 02 Nov 2020
A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning Hongjun Wang Guanbin Li Xiaobai Liu Liang Lin GAN AAML 21 22 0 15 Oct 2020
A Unified Approach to Interpreting and Boosting Adversarial Transferability Xin Wang Jie Ren Shuyu Lin Xiangming Zhu Yisen Wang Quanshi Zhang AAML 29 94 0 08 Oct 2020
Neural Bootstrapper Minsuk Shin Hyungjoon Cho Hyun-Seok Min Sungbin Lim UQCV BDL 22 7 0 02 Oct 2020
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective G. R. Machado Eugênio Silva R. Goldschmidt AAML 33 157 0 08 Sep 2020
Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks Wei-An Lin Chun Pong Lau Alexander Levine Ramalingam Chellappa S. Feizi AAML 81 60 0 05 Sep 2020