Certifying Some Distributional Robustness with Principled Adversarial Training

29 October 2017

Papers citing "Certifying Some Distributional Robustness with Principled Adversarial Training"

50 / 166 papers shown

Title
Rethinking Non-idealities in Memristive Crossbars for Adversarial Robustness in Neural Networks Abhiroop Bhattacharjee Priyadarshini Panda AAML 20 19 0 25 Aug 2020
Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems Aman Sinha Matthew O'Kelly Russ Tedrake John C. Duchi 39 47 0 24 Aug 2020
Robust Validation: Confident Predictions Even When Distributions Shift Maxime Cauchois Suyash Gupta Alnur Ali John C. Duchi OOD 11 89 0 10 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 25 73 0 07 Aug 2020
Distributionally Robust Losses for Latent Covariate Mixtures John C. Duchi Tatsunori Hashimoto Hongseok Namkoong 11 79 0 28 Jul 2020
Measuring Robustness to Natural Distribution Shifts in Image Classification Rohan Taori Achal Dave Vaishaal Shankar Nicholas Carlini Benjamin Recht Ludwig Schmidt OOD 22 530 0 01 Jul 2020
A Le Cam Type Bound for Adversarial Learning and Applications Qiuling Xu Kevin Bello Jean Honorio AAML 16 1 0 01 Jul 2020
Counterexample-Guided Learning of Monotonic Neural Networks Aishwarya Sivaraman G. Farnadi T. Millstein Guy Van den Broeck 16 50 0 16 Jun 2020
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them Chen Liu Mathieu Salzmann Tao R. Lin Ryota Tomioka Sabine Süsstrunk AAML 19 81 0 15 Jun 2020
A Stochastic Subgradient Method for Distributionally Robust Non-Convex Learning Mert Gurbuzbalaban A. Ruszczynski Landi Zhu 13 9 0 08 Jun 2020
Distributionally Robust Weighted $k$ -Nearest Neighbors Shixiang Zhu Liyan Xie Minghe Zhang Rui Gao Yao Xie OOD 21 7 0 07 Jun 2020
Robust Reinforcement Learning with Wasserstein Constraint Linfang Hou Liang Pang Xin Hong Yanyan Lan Zhiming Ma Dawei Yin 14 24 0 01 Jun 2020
Calibrated Surrogate Losses for Adversarially Robust Classification Han Bao Clayton Scott Masashi Sugiyama 14 45 0 28 May 2020
Learning to Learn Single Domain Generalization Fengchun Qiao Long Zhao Xi Peng OOD 29 431 0 30 Mar 2020
Auditing ML Models for Individual Bias and Unfairness Songkai Xue Mikhail Yurochkin Yuekai Sun MLAU 40 22 0 11 Mar 2020
FormulaZero: Distributionally Robust Online Adaptation via Offline Population Synthesis Aman Sinha Matthew O'Kelly Hongrui Zheng Rahul Mangharam John C. Duchi Russ Tedrake OffRL 66 26 0 09 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 50 63 0 02 Mar 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 215 901 0 02 Mar 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 24 785 0 26 Feb 2020
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh 6 78 0 24 Feb 2020
Global Convergence and Variance-Reduced Optimization for a Class of Nonconvex-Nonconcave Minimax Problems Junchi Yang Negar Kiyavash Niao He 23 83 0 22 Feb 2020
Adversarial Robustness for Code Pavol Bielik Martin Vechev AAML 9 89 0 11 Feb 2020
Universal Adversarial Attack on Attention and the Resulting Dataset DAmageNet Sizhe Chen Zhengbao He Chengjin Sun Jie-jin Yang Xiaolin Huang AAML 29 103 0 16 Jan 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 43 1,158 0 12 Jan 2020
Distributionally Robust Deep Learning using Hardness Weighted Sampling Lucas Fidon Michael Aertsen Thomas Deprest Doaa Emam Frédéric Guffens ... Andrew Melbourne Sébastien Ourselin Jan Deprest Georg Langs Tom Kamiel Magda Vercauteren OOD 14 10 0 08 Jan 2020
One Man's Trash is Another Man's Treasure: Resisting Adversarial Examples by Adversarial Examples Chang Xiao Changxi Zheng AAML 17 19 0 25 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 13 103 0 13 Nov 2019
Enhancing Certifiable Robustness via a Deep Model Ensemble Huan Zhang Minhao Cheng Cho-Jui Hsieh 25 9 0 31 Oct 2019
A First-Order Algorithmic Framework for Wasserstein Distributionally Robust Logistic Regression Jiajin Li Sen Huang Anthony Man-Cho So OOD 14 12 0 28 Oct 2019
Understanding and Quantifying Adversarial Examples Existence in Linear Classification Xupeng Shi A. Ding AAML 14 3 0 27 Oct 2019
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts Yu Sun Xiaolong Wang Zhuang Liu John Miller Alexei A. Efros Moritz Hardt TTA OOD 21 91 0 29 Sep 2019
On the Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost Zhuoran Yang Yongxin Chen Mingyi Hong Zhaoran Wang 24 39 0 14 Jul 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 27 2,152 0 05 Jul 2019
Distributionally Robust Counterfactual Risk Minimization Louis Faury Ugo Tanielian Flavian Vasile E. Smirnova Elvis Dohmatob 11 45 0 14 Jun 2019
Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang Tianyun Zhang Sijia Liu Pin-Yu Chen Jiacen Xu M. Fardad B. Li AAML 25 35 0 09 Jun 2019
Robustness for Non-Parametric Classification: A Generic Attack and Defense Yao-Yuan Yang Cyrus Rashtchian Yizhen Wang Kamalika Chaudhuri SILM AAML 26 42 0 07 Jun 2019
Robustness to Adversarial Perturbations in Learning from Incomplete Data Amir Najafi S. Maeda Masanori Koyama Takeru Miyato OOD 8 129 0 24 May 2019
Interpreting Adversarially Trained Convolutional Neural Networks Tianyuan Zhang Zhanxing Zhu AAML GAN FAtt 25 157 0 23 May 2019
Tutorial: Safe and Reliable Machine Learning S. Saria Adarsh Subbaswamy FaML 23 82 0 15 Apr 2019
Interpreting Adversarial Examples by Activation Promotion and Suppression Kaidi Xu Sijia Liu Gaoyuan Zhang Mengshu Sun Pu Zhao Quanfu Fan Chuang Gan X. Lin AAML FAtt 12 43 0 03 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 9 151 0 01 Apr 2019
Variational Inference with Latent Space Quantization for Adversarial Resilience Vinay Kyatham P. PrathoshA. Tarun Kumar Yadav Deepak Mishra Dheeraj Mundhra AAML 16 3 0 24 Mar 2019
Interpreting Neural Networks Using Flip Points Roozbeh Yousefzadeh D. O’Leary AAML FAtt 19 17 0 21 Mar 2019
Semantics Preserving Adversarial Learning Ousmane Amadou Dia Elnaz Barshan Reza Babanezhad AAML GAN 21 2 0 10 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 22 62 0 05 Mar 2019
A Fundamental Performance Limitation for Adversarial Classification Abed AlRahman Al Makdah Vaibhav Katewa Fabio Pasqualetti AAML 17 8 0 04 Mar 2019
Theoretical Analysis of Adversarial Learning: A Minimax Approach Zhuozhuo Tu Jingwei Zhang Dacheng Tao AAML 11 68 0 13 Nov 2018
MixTrain: Scalable Training of Verifiably Robust Neural Networks Yue Zhang Yizheng Chen Ahmed Abdou M. Guizani AAML 16 23 0 06 Nov 2018
Weakly-Convex Concave Min-Max Optimization: Provable Algorithms and Applications in Machine Learning Hassan Rafique Mingrui Liu Qihang Lin Tianbao Yang 15 107 0 04 Oct 2018
A Kernel Perspective for Regularizing Deep Neural Networks A. Bietti Grégoire Mialon Dexiong Chen Julien Mairal 11 15 0 30 Sep 2018