Extending Defensive Distillation

15 May 2017

Papers citing "Extending Defensive Distillation"

28 / 28 papers shown

Title
TAET: Two-Stage Adversarial Equalization Training on Long-Tailed Distributions Wang YuHang Junkang Guo Aolei Liu Kaihao Wang Zaitong Wu Zhenyu Liu Wenfei Yin Jian Liu AAML 50 0 0 02 Mar 2025
A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks Yang Wang B. Dong Ke Xu Haiyin Piao Yufei Ding Baocai Yin Xin Yang AAML 37 3 0 10 Oct 2023
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses Joana Cabral Costa Tiago Roxo Hugo Manuel Proença Pedro R. M. Inácio AAML 37 49 0 18 May 2023
Adversarial Amendment is the Only Force Capable of Transforming an Enemy into a Friend Chong Yu Tao Chen Zhongxue Gan AAML 15 1 0 18 May 2023
A Tutorial on Adversarial Learning Attacks and Countermeasures Cato Pauling Michael Gimson Muhammed Qaid Ahmad Kida Basel Halak AAML 17 11 0 21 Feb 2022
Mixing between the Cross Entropy and the Expectation Loss Terms Barak Battash Lior Wolf Tamir Hazan UQCV 20 0 0 12 Sep 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
Robust Pre-Training by Adversarial Contrastive Learning Ziyu Jiang Tianlong Chen Ting-Li Chen Zhangyang Wang 30 226 0 26 Oct 2020
A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning Hongjun Wang Guanbin Li Xiaobai Liu Liang Lin GAN AAML 16 22 0 15 Oct 2020
Adversarially Robust Neural Architectures Minjing Dong Yanxi Li Yunhe Wang Chang Xu AAML OOD 36 48 0 02 Sep 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
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness Ahmadreza Jeddi M. Shafiee Michelle Karg C. Scharfenberger A. Wong OOD AAML 58 63 0 02 Mar 2020
REFIT: A Unified Watermark Removal Framework For Deep Learning Systems With Limited Data Xinyun Chen Wenxiao Wang Chris Bender Yiming Ding R. Jia Bo-wen Li D. Song AAML 19 106 0 17 Nov 2019
Domain Robustness in Neural Machine Translation Mathias Müller Annette Rios Gonzales Rico Sennrich 13 95 0 08 Nov 2019
Toward Robust Image Classification Basemah Alshemali Alta Graham Jugal Kalita AAML 29 6 0 19 Sep 2019
Enhancing Gradient-based Attacks with Symbolic Intervals Shiqi Wang Yizheng Chen Ahmed Abdou Suman Jana AAML 17 15 0 05 Jun 2019
Testing DNN Image Classifiers for Confusion & Bias Errors Yuchi Tian Ziyuan Zhong Vicente Ordonez Gail E. Kaiser Baishakhi Ray 24 52 0 20 May 2019
Scalable Differential Privacy with Certified Robustness in Adversarial Learning Nhathai Phan My T. Thai Han Hu R. Jin Tong Sun Dejing Dou 27 14 0 23 Mar 2019
Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search Abhimanyu Dubey L. V. D. van der Maaten Zeki Yalniz Yixuan Li D. Mahajan AAML 25 62 0 05 Mar 2019
Defending Against Universal Perturbations With Shared Adversarial Training Chaithanya Kumar Mummadi Thomas Brox J. H. Metzen AAML 18 60 0 10 Dec 2018
MixTrain: Scalable Training of Verifiably Robust Neural Networks Yue Zhang Yizheng Chen Ahmed Abdou M. Guizani AAML 19 23 0 06 Nov 2018
Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing Jingyi Wang Jun Sun Peixin Zhang Xinyu Wang AAML 19 41 0 14 May 2018
Attacking Binarized Neural Networks A. Galloway Graham W. Taylor M. Moussa MQ AAML 14 104 0 01 Nov 2017
Detecting Adversarial Attacks on Neural Network Policies with Visual Foresight Yen-Chen Lin Ming-Yu Liu Min Sun Jia-Bin Huang AAML 21 48 0 02 Oct 2017
DeepXplore: Automated Whitebox Testing of Deep Learning Systems Kexin Pei Yinzhi Cao Junfeng Yang Suman Jana AAML 25 1,351 0 18 May 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 231 1,837 0 03 Feb 2017
Safety Verification of Deep Neural Networks Xiaowei Huang M. Kwiatkowska Sen Wang Min Wu AAML 180 932 0 21 Oct 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015