Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality

8 January 2018

Papers citing "Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality"

50 / 150 papers shown

Title
Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability Kaizhao Liang Jacky Y. Zhang Wei Ping Zhuolin Yang Oluwasanmi Koyejo Yangqiu Song AAML 33 25 0 25 Jun 2020
AdvMind: Inferring Adversary Intent of Black-Box Attacks Ren Pang Xinyang Zhang S. Ji Xiapu Luo Ting Wang MLAU AAML 11 29 0 16 Jun 2020
Tricking Adversarial Attacks To Fail Blerta Lindqvist AAML 10 0 0 08 Jun 2020
Exploring the role of Input and Output Layers of a Deep Neural Network in Adversarial Defense Jay N. Paranjape R. Dubey Vijendran V. Gopalan AAML 19 2 0 02 Jun 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 37 147 0 20 May 2020
DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses Yaxin Li Wei Jin Han Xu Jiliang Tang AAML 32 131 0 13 May 2020
Ensemble Generative Cleaning with Feedback Loops for Defending Adversarial Attacks Jianhe Yuan Zhihai He AAML 29 22 0 23 Apr 2020
Single-step Adversarial training with Dropout Scheduling S. VivekB. R. Venkatesh Babu OOD AAML 18 71 0 18 Apr 2020
DaST: Data-free Substitute Training for Adversarial Attacks Mingyi Zhou Jing Wu Yipeng Liu Shuaicheng Liu Ce Zhu 22 142 0 28 Mar 2020
Anomalous Example Detection in Deep Learning: A Survey Saikiran Bulusu B. Kailkhura Bo-wen Li P. Varshney D. Song AAML 28 47 0 16 Mar 2020
Adversarial Camouflage: Hiding Physical-World Attacks with Natural Styles Ranjie Duan Xingjun Ma Yisen Wang James Bailey •. A. K. Qin Yun Yang AAML 167 224 0 08 Mar 2020
Deflecting Adversarial Attacks Yao Qin Nicholas Frosst Colin Raffel G. Cottrell Geoffrey E. Hinton AAML 30 15 0 18 Feb 2020
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets Dongxian Wu Yisen Wang Shutao Xia James Bailey Xingjun Ma AAML SILM 25 310 0 14 Feb 2020
One Man's Trash is Another Man's Treasure: Resisting Adversarial Examples by Adversarial Examples Chang Xiao Changxi Zheng AAML 25 19 0 25 Nov 2019
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models Tong Che Xiaofeng Liu Site Li Yubin Ge Ruixiang Zhang Caiming Xiong Yoshua Bengio 38 52 0 18 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 18 104 0 13 Nov 2019
Detection of Adversarial Attacks and Characterization of Adversarial Subspace Mohammad Esmaeilpour P. Cardinal Alessandro Lameiras Koerich AAML 27 17 0 26 Oct 2019
A New Defense Against Adversarial Images: Turning a Weakness into a Strength Tao Yu Shengyuan Hu Chuan Guo Wei-Lun Chao Kilian Q. Weinberger AAML 58 101 0 16 Oct 2019
Toward Robust Image Classification Basemah Alshemali Alta Graham Jugal Kalita AAML 40 6 0 19 Sep 2019
Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks Ka-Ho Chow Wenqi Wei Yanzhao Wu Ling Liu AAML 22 15 0 21 Aug 2019
Subspace Determination through Local Intrinsic Dimensional Decomposition: Theory and Experimentation R. Becker Imane Hafnaoui Michael E. Houle Pan Li Arthur Zimek 14 8 0 15 Jul 2019
Evolving Robust Neural Architectures to Defend from Adversarial Attacks Shashank Kotyan Danilo Vasconcellos Vargas OOD AAML 24 36 0 27 Jun 2019
Defending Against Adversarial Examples with K-Nearest Neighbor Chawin Sitawarin David Wagner AAML 8 29 0 23 Jun 2019
ML-LOO: Detecting Adversarial Examples with Feature Attribution Puyudi Yang Jianbo Chen Cho-Jui Hsieh Jane-ling Wang Michael I. Jordan AAML 22 101 0 08 Jun 2019
Enhancing Gradient-based Attacks with Symbolic Intervals Shiqi Wang Yizheng Chen Ahmed Abdou Suman Jana AAML 28 15 0 05 Jun 2019
Purifying Adversarial Perturbation with Adversarially Trained Auto-encoders Hebi Li Qi Xiao Shixin Tian Jin Tian AAML 24 4 0 26 May 2019
Enhancing Adversarial Defense by k-Winners-Take-All Chang Xiao Peilin Zhong Changxi Zheng AAML 24 97 0 25 May 2019
Adversarial Training for Free! Ali Shafahi Mahyar Najibi Amin Ghiasi Zheng Xu John P. Dickerson Christoph Studer L. Davis Gavin Taylor Tom Goldstein AAML 68 1,227 0 29 Apr 2019
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations Saeid Asgari Taghanaki Kumar Abhishek Shekoofeh Azizi Ghassan Hamarneh AAML 31 40 0 03 Mar 2019
Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN Ke Sun Zhanxing Zhu Zhouchen Lin AAML 19 20 0 28 Feb 2019
Adversarial Attack and Defense on Point Sets Jiancheng Yang Qiang Zhang Rongyao Fang Bingbing Ni Jinxian Liu Qi Tian 3DPC 24 122 0 28 Feb 2019
Daedalus: Breaking Non-Maximum Suppression in Object Detection via Adversarial Examples Derui Wang Chaoran Li S. Wen Qing-Long Han Surya Nepal Xiangyu Zhang Yang Xiang AAML 30 40 0 06 Feb 2019
The Limitations of Adversarial Training and the Blind-Spot Attack Huan Zhang Hongge Chen Zhao Song Duane S. Boning Inderjit S. Dhillon Cho-Jui Hsieh AAML 19 144 0 15 Jan 2019
Interpretable Deep Learning under Fire Xinyang Zhang Ningfei Wang Hua Shen S. Ji Xiapu Luo Ting Wang AAML AI4CE 24 169 0 03 Dec 2018
MixTrain: Scalable Training of Verifiably Robust Neural Networks Yue Zhang Yizheng Chen Ahmed Abdou Mohsen Guizani AAML 21 23 0 06 Nov 2018
Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation Chaowei Xiao Ruizhi Deng Bo-wen Li Feng Yu M. Liu D. Song AAML 16 99 0 11 Oct 2018
On The Utility of Conditional Generation Based Mutual Information for Characterizing Adversarial Subspaces Chia-Yi Hsu Pei-Hsuan Lu Pin-Yu Chen Chia-Mu Yu AAML 30 1 0 24 Sep 2018
Distributionally Adversarial Attack T. Zheng Changyou Chen K. Ren OOD 21 121 0 16 Aug 2018
Motivating the Rules of the Game for Adversarial Example Research Justin Gilmer Ryan P. Adams Ian Goodfellow David G. Andersen George E. Dahl AAML 50 226 0 18 Jul 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 23 1,997 0 10 Jul 2018
Adversarial Examples in Deep Learning: Characterization and Divergence Wenqi Wei Ling Liu Margaret Loper Stacey Truex Lei Yu Mehmet Emre Gursoy Yanzhao Wu AAML SILM 33 18 0 29 Jun 2018
Dimensionality-Driven Learning with Noisy Labels Xingjun Ma Yisen Wang Michael E. Houle Shuo Zhou S. Erfani Shutao Xia S. Wijewickrema James Bailey NoLa 35 425 0 07 Jun 2018
AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning Jinyuan Jia Neil Zhenqiang Gong AAML 13 161 0 13 May 2018
On the Limitation of Local Intrinsic Dimensionality for Characterizing the Subspaces of Adversarial Examples Pei-Hsuan Lu Pin-Yu Chen Chia-Mu Yu AAML 9 26 0 26 Mar 2018
Defending against Adversarial Attack towards Deep Neural Networks via Collaborative Multi-task Training Derui Wang Chaoran Li S. Wen Surya Nepal Yang Xiang AAML 38 29 0 14 Mar 2018
High Dimensional Spaces, Deep Learning and Adversarial Examples S. Dube 37 29 0 02 Jan 2018
Generative Adversarial Perturbations Omid Poursaeed Isay Katsman Bicheng Gao Serge J. Belongie AAML GAN WIGM 31 351 0 06 Dec 2017
Towards Robust Neural Networks via Random Self-ensemble Xuanqing Liu Minhao Cheng Huan Zhang Cho-Jui Hsieh FedML AAML 43 418 0 02 Dec 2017
DeepFense: Online Accelerated Defense Against Adversarial Deep Learning B. Rouhani Mohammad Samragh Mojan Javaheripi T. Javidi F. Koushanfar AAML 12 15 0 08 Sep 2017
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 293 5,842 0 08 Jul 2016