Certifying Some Distributional Robustness with Principled Adversarial Training

29 October 2017

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

50 / 240 papers shown

Title
Robust Reinforcement Learning with Wasserstein Constraint Linfang Hou Liang Pang Xin Hong Yanyan Lan Zhiming Ma Dawei Yin 27 24 0 01 Jun 2020
Adversarial Classification via Distributional Robustness with Wasserstein Ambiguity Nam Ho-Nguyen Stephen J. Wright OOD 50 16 0 28 May 2020
Calibrated Surrogate Losses for Adversarially Robust Classification Han Bao Clayton Scott Masashi Sugiyama 29 45 0 28 May 2020
Adversarial Training against Location-Optimized Adversarial Patches Sukrut Rao David Stutz Bernt Schiele AAML 19 91 0 05 May 2020
Robust Deep Learning as Optimal Control: Insights and Convergence Guarantees Jacob H. Seidman Mahyar Fazlyab V. Preciado George J. Pappas AAML 16 15 0 01 May 2020
Learning to Learn Single Domain Generalization Fengchun Qiao Long Zhao Xi Peng OOD 54 433 0 30 Mar 2020
Safety-Aware Hardening of 3D Object Detection Neural Network Systems Chih-Hong Cheng 3DPC 27 12 0 25 Mar 2020
Adversarial Attacks on Monocular Depth Estimation Ziqi Zhang Xinge Zhu Yingwei Li Xiangqun Chen Yao Guo AAML MDE 30 25 0 23 Mar 2020
When are Non-Parametric Methods Robust? Robi Bhattacharjee Kamalika Chaudhuri AAML 42 28 0 13 Mar 2020
Auditing ML Models for Individual Bias and Unfairness Songkai Xue Mikhail Yurochkin Yuekai Sun MLAU 40 23 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 27 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 69 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 215 907 0 02 Mar 2020
Improving Robustness of Deep-Learning-Based Image Reconstruction Ankit Raj Y. Bresler Bo-wen Li OOD AAML 29 50 0 26 Feb 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 47 787 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 24 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 25 83 0 22 Feb 2020
Distributionally Robust Bayesian Optimization Johannes Kirschner Ilija Bogunovic Stefanie Jegelka Andreas Krause 30 77 0 20 Feb 2020
Adversarial Robustness for Code Pavol Bielik Martin Vechev AAML 22 89 0 11 Feb 2020
Near-Optimal Algorithms for Minimax Optimization Tianyi Lin Chi Jin Michael I. Jordan 34 251 0 05 Feb 2020
Universal Adversarial Attack on Attention and the Resulting Dataset DAmageNet Sizhe Chen Zhengbao He Chengjin Sun Jie-jin Yang Xiaolin Huang AAML 31 104 0 16 Jan 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 99 1,159 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 22 10 0 08 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
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization Shiori Sagawa Pang Wei Koh Tatsunori B. Hashimoto Percy Liang OOD 16 1,198 0 20 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
Enhancing Certifiable Robustness via a Deep Model Ensemble Huan Zhang Minhao Cheng Cho-Jui Hsieh 33 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 30 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
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
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 27 92 0 29 Sep 2019
Distributionally Robust Optimization: A Review Hamed Rahimian Sanjay Mehrotra 19 118 0 13 Aug 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 32 39 0 14 Jul 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 72 2,161 0 05 Jul 2019
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness Fanny Yang Zuowen Wang C. Heinze-Deml 28 42 0 26 Jun 2019
Distributionally Robust Counterfactual Risk Minimization Louis Faury Ugo Tanielian Flavian Vasile E. Smirnova Elvis Dohmatob 20 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 Yangqiu Song 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 34 42 0 07 Jun 2019
Confidence Regions in Wasserstein Distributionally Robust Estimation Jose H. Blanchet Karthyek Murthy Nian Si OOD 21 57 0 04 Jun 2019
Privacy Risks of Securing Machine Learning Models against Adversarial Examples Liwei Song Reza Shokri Prateek Mittal SILM MIACV AAML 6 235 0 24 May 2019
Robustness to Adversarial Perturbations in Learning from Incomplete Data Amir Najafi S. Maeda Masanori Koyama Takeru Miyato OOD 24 129 0 24 May 2019
Robust Attribution Regularization Jiefeng Chen Xi Wu Vaibhav Rastogi Yingyu Liang S. Jha OOD 9 83 0 23 May 2019
Interpreting Adversarially Trained Convolutional Neural Networks Tianyuan Zhang Zhanxing Zhu AAML GAN FAtt 28 158 0 23 May 2019
Tutorial: Safe and Reliable Machine Learning Suchi Saria Adarsh Subbaswamy FaML 30 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 24 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 17 151 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 19 3 0 24 Mar 2019
Interpreting Neural Networks Using Flip Points Roozbeh Yousefzadeh D. O’Leary AAML FAtt 22 17 0 21 Mar 2019
Semantics Preserving Adversarial Learning Ousmane Amadou Dia Elnaz Barshan Reza Babanezhad AAML GAN 29 2 0 10 Mar 2019