Stochastic Activation Pruning for Robust Adversarial Defense

5 March 2018

Guneet Singh Dhillon

Kamyar Azizzadenesheli

Papers citing "Stochastic Activation Pruning for Robust Adversarial Defense"

50 / 120 papers shown

Title
Improving Global Adversarial Robustness Generalization With Adversarially Trained GAN Desheng Wang Wei-dong Jin Yunpu Wu Aamir Khan GAN 36 8 0 08 Mar 2021
Lost in Pruning: The Effects of Pruning Neural Networks beyond Test Accuracy Lucas Liebenwein Cenk Baykal Brandon Carter David K Gifford Daniela Rus AAML 40 71 0 04 Mar 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training Vasu Singla Sahil Singla David Jacobs S. Feizi AAML 32 45 0 15 Feb 2021
Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPS Felix O. Olowononi D. Rawat Chunmei Liu 34 132 0 14 Feb 2021
Mixed Nash Equilibria in the Adversarial Examples Game Laurent Meunier M. Scetbon Rafael Pinot Jamal Atif Y. Chevaleyre AAML 23 29 0 13 Feb 2021
"What's in the box?!": Deflecting Adversarial Attacks by Randomly Deploying Adversarially-Disjoint Models Sahar Abdelnabi Mario Fritz AAML 27 7 0 09 Feb 2021
GAN Inversion: A Survey Weihao Xia Yulun Zhang Yujiu Yang Jing-Hao Xue Bolei Zhou Ming-Hsuan Yang DiffM 70 507 0 14 Jan 2021
Local Competition and Stochasticity for Adversarial Robustness in Deep Learning Konstantinos P. Panousis S. Chatzis Antonios Alexos Sergios Theodoridis BDL AAML OOD 56 19 0 04 Jan 2021
ROBY: Evaluating the Robustness of a Deep Model by its Decision Boundaries Jinyin Chen Zhen Wang Haibin Zheng Jun Xiao Zhaoyan Ming AAML 19 5 0 18 Dec 2020
Robustness and Transferability of Universal Attacks on Compressed Models Alberto G. Matachana Kenneth T. Co Luis Muñoz-González David Martínez Emil C. Lupu AAML 29 10 0 10 Dec 2020
Learnable Boundary Guided Adversarial Training Jiequan Cui Shu Liu Liwei Wang Jiaya Jia OOD AAML 30 124 0 23 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 13 24 0 15 Nov 2020
Robust Pre-Training by Adversarial Contrastive Learning Ziyu Jiang Tianlong Chen Ting-Li Chen Zhangyang Wang 30 227 0 26 Oct 2020
Certifying Confidence via Randomized Smoothing Aounon Kumar Alexander Levine S. Feizi Tom Goldstein UQCV 33 39 0 17 Sep 2020
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective G. R. Machado Eugênio Silva R. Goldschmidt AAML 33 156 0 08 Sep 2020
Rethinking Non-idealities in Memristive Crossbars for Adversarial Robustness in Neural Networks Abhiroop Bhattacharjee Priyadarshini Panda AAML 28 19 0 25 Aug 2020
Addressing Neural Network Robustness with Mixup and Targeted Labeling Adversarial Training Alfred Laugros A. Caplier Matthieu Ospici AAML 24 19 0 19 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 27 73 0 07 Aug 2020
RANDOM MASK: Towards Robust Convolutional Neural Networks Tiange Luo Tianle Cai Mengxiao Zhang Siyu Chen Liwei Wang AAML OOD 19 17 0 27 Jul 2020
AdvFoolGen: Creating Persistent Troubles for Deep Classifiers Yuzhen Ding Nupur Thakur Baoxin Li AAML 24 3 0 20 Jul 2020
Adversarial Example Games A. Bose Gauthier Gidel Hugo Berrard Andre Cianflone Pascal Vincent Simon Lacoste-Julien William L. Hamilton AAML GAN 38 51 0 01 Jul 2020
SPLASH: Learnable Activation Functions for Improving Accuracy and Adversarial Robustness Mohammadamin Tavakoli Forest Agostinelli Pierre Baldi AAML FAtt 36 39 0 16 Jun 2020
Defensive Approximation: Securing CNNs using Approximate Computing Amira Guesmi Ihsen Alouani Khaled N. Khasawneh M. Baklouti T. Frikha Mohamed Abid Nael B. Abu-Ghazaleh AAML 19 37 0 13 Jun 2020
Tricking Adversarial Attacks To Fail Blerta Lindqvist AAML 10 0 0 08 Jun 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
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning Tianlong Chen Sijia Liu Shiyu Chang Yu Cheng Lisa Amini Zhangyang Wang AAML 18 246 0 28 Mar 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
Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-Linear Activations Saima Sharmin Nitin Rathi Priyadarshini Panda Kaushik Roy AAML 116 86 0 23 Mar 2020
Towards Practical Lottery Ticket Hypothesis for Adversarial Training Bai Li Shiqi Wang Yunhan Jia Yantao Lu Zhenyu Zhong Lawrence Carin Suman Jana AAML 26 14 0 06 Mar 2020
On Adaptive Attacks to Adversarial Example Defenses Florian Tramèr Nicholas Carlini Wieland Brendel A. Madry AAML 104 822 0 19 Feb 2020
Towards Sharper First-Order Adversary with Quantized Gradients Zhuanghua Liu Ivor W. Tsang AAML 19 0 0 01 Feb 2020
GhostImage: Remote Perception Attacks against Camera-based Image Classification Systems Yanmao Man Ming Li Ryan M. Gerdes AAML 14 8 0 21 Jan 2020
Benchmarking Adversarial Robustness Yinpeng Dong Qi-An Fu Xiao Yang Tianyu Pang Hang Su Zihao Xiao Jun Zhu AAML 28 36 0 26 Dec 2019
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
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
Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets Yogesh Balaji Tom Goldstein Judy Hoffman AAML 134 103 0 17 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
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 24 18 0 27 Sep 2019
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks Sekitoshi Kanai Yasutoshi Ida Yasuhiro Fujiwara Masanori Yamada S. Adachi AAML 20 1 0 19 Sep 2019
Towards Quality Assurance of Software Product Lines with Adversarial Configurations Paul Temple M. Acher Gilles Perrouin Battista Biggio J. Jézéquel Fabio Roli AAML 16 11 0 16 Sep 2019
Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses Tianlin Li Siyue Wang Pin-Yu Chen Yanzhi Wang Brian Kulis Xue Lin S. Chin AAML 16 42 0 20 Aug 2019
BlurNet: Defense by Filtering the Feature Maps Ravi Raju Mikko H. Lipasti AAML 39 15 0 06 Aug 2019
Are Adversarial Perturbations a Showstopper for ML-Based CAD? A Case Study on CNN-Based Lithographic Hotspot Detection Kang Liu Haoyu Yang Yuzhe Ma Benjamin Tan Bei Yu Evangeline F. Y. Young Ramesh Karri S. Garg AAML 20 10 0 25 Jun 2019
Enhancing Transformation-based Defenses using a Distribution Classifier C. Kou H. Lee E. Chang Teck Khim Ng 34 3 0 01 Jun 2019
Robust Sparse Regularization: Simultaneously Optimizing Neural Network Robustness and Compactness Adnan Siraj Rakin Zhezhi He Li Yang Yanzhi Wang Liqiang Wang Deliang Fan AAML 40 21 0 30 May 2019
Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward A. Qayyum Muhammad Usama Junaid Qadir Ala I. Al-Fuqaha AAML 21 187 0 29 May 2019
Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss Pengcheng Li Jinfeng Yi Bowen Zhou Lijun Zhang AAML 31 36 0 28 May 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