Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients

26 November 2017

Finale Doshi-Velez

Papers citing "Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients"

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Title
Exploring Transferable and Robust Adversarial Perturbation Generation from the Perspective of Network Hierarchy Ruikui Wang Yuanfang Guo Ruijie Yang Yunhong Wang AAML 17 3 0 16 Aug 2021
Improving the trustworthiness of image classification models by utilizing bounding-box annotations K. Dharma Chicheng Zhang 29 5 0 15 Aug 2021
Synthetic Benchmarks for Scientific Research in Explainable Machine Learning Yang Liu Sujay Khandagale Colin White W. Neiswanger 37 65 0 23 Jun 2021
Towards Robust Classification Model by Counterfactual and Invariant Data Generation C. Chang George Adam Anna Goldenberg OOD CML 27 31 0 02 Jun 2021
Knowledge Distillation as Semiparametric Inference Tri Dao G. Kamath Vasilis Syrgkanis Lester W. Mackey 34 31 0 20 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 32 65 0 09 Apr 2021
White Box Methods for Explanations of Convolutional Neural Networks in Image Classification Tasks Meghna P. Ayyar J. Benois-Pineau A. Zemmari FAtt 9 17 0 06 Apr 2021
Mitigating Gradient-based Adversarial Attacks via Denoising and Compression Rehana Mahfuz R. Sahay Aly El Gamal AAML 6 3 0 03 Apr 2021
SoK: A Modularized Approach to Study the Security of Automatic Speech Recognition Systems Yuxuan Chen Jiangshan Zhang Xuejing Yuan Shengzhi Zhang Kai Chen Xiaofeng Wang Shanqing Guo AAML 37 15 0 19 Mar 2021
Improving Global Adversarial Robustness Generalization With Adversarially Trained GAN Desheng Wang Wei-dong Jin Yunpu Wu Aamir Khan GAN 30 8 0 08 Mar 2021
Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack Mengting Xu Tao Zhang Zhongnian Li Mingxia Liu Daoqiang Zhang AAML OOD MedIm 25 41 0 05 Mar 2021
Do Input Gradients Highlight Discriminative Features? Harshay Shah Prateek Jain Praneeth Netrapalli AAML FAtt 21 57 0 25 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
Connecting Interpretability and Robustness in Decision Trees through Separation Michal Moshkovitz Yao-Yuan Yang Kamalika Chaudhuri 30 22 0 14 Feb 2021
Understanding and Increasing Efficiency of Frank-Wolfe Adversarial Training Theodoros Tsiligkaridis Jay Roberts AAML 17 11 0 22 Dec 2020
On the human-recognizability phenomenon of adversarially trained deep image classifiers Jonathan W. Helland Nathan M. VanHoudnos AAML 22 4 0 18 Dec 2020
On 1/n neural representation and robustness Josue Nassar Piotr A. Sokól SueYeon Chung K. Harris Il Memming Park AAML OOD 24 23 0 08 Dec 2020
The Vulnerability of the Neural Networks Against Adversarial Examples in Deep Learning Algorithms Rui Zhao AAML 21 1 0 02 Nov 2020
The State of Industrial Robotics: Emerging Technologies, Challenges, and Key Research Directions Lindsay M. Sanneman Christopher K. Fourie J. Shah 16 64 0 27 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 29 48 0 19 Oct 2020
Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers Hanjie Chen Yangfeng Ji AAML VLM 13 63 0 01 Oct 2020
Input Hessian Regularization of Neural Networks Waleed Mustafa Robert A. Vandermeulen Marius Kloft AAML 17 12 0 14 Sep 2020
Play MNIST For Me! User Studies on the Effects of Post-Hoc, Example-Based Explanations & Error Rates on Debugging a Deep Learning, Black-Box Classifier Courtney Ford Eoin M. Kenny Mark T. Keane 23 6 0 10 Sep 2020
Backpropagated Gradient Representations for Anomaly Detection Gukyeong Kwon Mohit Prabhushankar Dogancan Temel Ghassan AlRegib 12 71 0 18 Jul 2020
Proper Network Interpretability Helps Adversarial Robustness in Classification Akhilan Boopathy Sijia Liu Gaoyuan Zhang Cynthia Liu Pin-Yu Chen Shiyu Chang Luca Daniel AAML FAtt 19 66 0 26 Jun 2020
Knowledge Distillation: A Survey Jianping Gou B. Yu Stephen J. Maybank Dacheng Tao VLM 19 2,843 0 09 Jun 2020
Improve robustness of DNN for ECG signal classification:a noise-to-signal ratio perspective Linhai Ma Liang Liang AAML 8 4 0 18 May 2020
Adversarial Latent Autoencoders Stanislav Pidhorskyi Donald Adjeroh Gianfranco Doretto GAN DRL 40 259 0 09 Apr 2020
Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization Saehyung Lee Hyungyu Lee Sungroh Yoon AAML 161 113 0 05 Mar 2020
Uncertainty Estimation Using a Single Deep Deterministic Neural Network Joost R. van Amersfoort Lewis Smith Yee Whye Teh Y. Gal UQCV BDL 14 55 0 04 Mar 2020
On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping Sanghyun Hong Varun Chandrasekaran Yigitcan Kaya Tudor Dumitras Nicolas Papernot AAML 20 136 0 26 Feb 2020
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence S. Raschka Joshua Patterson Corey J. Nolet AI4CE 24 483 0 12 Feb 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
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey Olakunle Ibitoye Rana Abou-Khamis Mohamed el Shehaby Ashraf Matrawy M. O. Shafiq AAML 26 68 0 06 Nov 2019
Adversarial Learning with Margin-based Triplet Embedding Regularization Yaoyao Zhong Weihong Deng AAML 17 50 0 20 Sep 2019
Complexity-Scalable Neural Network Based MIMO Detection With Learnable Weight Scaling A. Mohammad C. Masouros Y. Andreopoulos 18 28 0 12 Sep 2019
Improving performance of deep learning models with axiomatic attribution priors and expected gradients G. Erion Joseph D. Janizek Pascal Sturmfels Scott M. Lundberg Su-In Lee OOD BDL FAtt 18 80 0 25 Jun 2019
Controlling Neural Level Sets Matan Atzmon Niv Haim Lior Yariv Ofer Israelov Haggai Maron Y. Lipman AI4CE 22 118 0 28 May 2019
Scaleable input gradient regularization for adversarial robustness Chris Finlay Adam M. Oberman AAML 16 77 0 27 May 2019
Enhancing Adversarial Defense by k-Winners-Take-All Chang Xiao Peilin Zhong Changxi Zheng AAML 13 97 0 25 May 2019
Minimal Achievable Sufficient Statistic Learning Milan Cvitkovic Günther Koliander 17 12 0 19 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 33 1,227 0 29 Apr 2019
Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks Aamir Mustafa Salman Khan Munawar Hayat Roland Göcke Jianbing Shen Ling Shao AAML 17 151 0 01 Apr 2019
Defense-VAE: A Fast and Accurate Defense against Adversarial Attacks Xiang Li Shihao Ji AAML 19 26 0 17 Dec 2018
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 282 10,354 0 12 Dec 2018
MMA Training: Direct Input Space Margin Maximization through Adversarial Training G. Ding Yash Sharma Kry Yik-Chau Lui Ruitong Huang AAML 16 270 0 06 Dec 2018
Robustness via curvature regularization, and vice versa Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi J. Uesato P. Frossard AAML 21 318 0 23 Nov 2018
Stability-certified reinforcement learning: A control-theoretic perspective Ming Jin Javad Lavaei 28 85 0 26 Oct 2018
Efficient Two-Step Adversarial Defense for Deep Neural Networks Ting-Jui Chang Yukun He Peng Li AAML 25 11 0 08 Oct 2018
Interpreting Adversarial Robustness: A View from Decision Surface in Input Space Fuxun Yu Chenchen Liu Yanzhi Wang Liang Zhao Xiang Chen AAML OOD 31 27 0 29 Sep 2018