Certifying Some Distributional Robustness with Principled Adversarial Training

29 October 2017

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

40 / 240 papers shown

Title
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 33 62 0 05 Mar 2019
A Fundamental Performance Limitation for Adversarial Classification Abed AlRahman Al Makdah Vaibhav Katewa Fabio Pasqualetti AAML 33 8 0 04 Mar 2019
Enhancing the Robustness of Deep Neural Networks by Boundary Conditional GAN Ke Sun Zhanxing Zhu Zhouchen Lin AAML 19 20 0 28 Feb 2019
Robust Decision Trees Against Adversarial Examples Hongge Chen Huan Zhang Duane S. Boning Cho-Jui Hsieh AAML 22 116 0 27 Feb 2019
On the Sensitivity of Adversarial Robustness to Input Data Distributions G. Ding Kry Yik-Chau Lui Xiaomeng Jin Luyu Wang Ruitong Huang OOD 26 59 0 22 Feb 2019
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations Eric Wong Frank R. Schmidt J. Zico Kolter AAML 36 210 0 21 Feb 2019
On the (In)fidelity and Sensitivity for Explanations Chih-Kuan Yeh Cheng-Yu Hsieh A. Suggala David I. Inouye Pradeep Ravikumar FAtt 39 449 0 27 Jan 2019
The Limitations of Adversarial Training and the Blind-Spot Attack Huan Zhang Hongge Chen Zhao Song Duane S. Boning Inderjit S. Dhillon Cho-Jui Hsieh AAML 22 144 0 15 Jan 2019
Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport Adarsh Subbaswamy Peter F. Schulam Suchi Saria OOD 11 20 0 11 Dec 2018
Theoretical Analysis of Adversarial Learning: A Minimax Approach Zhuozhuo Tu Jingwei Zhang Dacheng Tao AAML 15 68 0 13 Nov 2018
MixTrain: Scalable Training of Verifiably Robust Neural Networks Yue Zhang Yizheng Chen Ahmed Abdou Mohsen Guizani AAML 21 23 0 06 Nov 2018
Stronger Data Poisoning Attacks Break Data Sanitization Defenses Pang Wei Koh Jacob Steinhardt Percy Liang 6 240 0 02 Nov 2018
Learning Models with Uniform Performance via Distributionally Robust Optimization John C. Duchi Hongseok Namkoong OOD 19 402 0 20 Oct 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 13 15 0 30 Sep 2018
Wasserstein Distributionally Robust Kalman Filtering Soroosh Shafieezadeh-Abadeh Viet Anh Nguyen Daniel Kuhn Peyman Mohajerin Esfahani 14 99 0 24 Sep 2018
Certified Adversarial Robustness with Additive Noise Bai Li Changyou Chen Wenlin Wang Lawrence Carin AAML 28 341 0 10 Sep 2018
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability Kai Y. Xiao Vincent Tjeng Nur Muhammad (Mahi) Shafiullah A. Madry AAML OOD 12 199 0 09 Sep 2018
Structured Adversarial Attack: Towards General Implementation and Better Interpretability Kaidi Xu Sijia Liu Pu Zhao Pin-Yu Chen Huan Zhang Quanfu Fan Deniz Erdogmus Yanzhi Wang X. Lin AAML 21 160 0 05 Aug 2018
Motivating the Rules of the Game for Adversarial Example Research Justin Gilmer Ryan P. Adams Ian Goodfellow David G. Andersen George E. Dahl AAML 50 226 0 18 Jul 2018
Monge blunts Bayes: Hardness Results for Adversarial Training Zac Cranko A. Menon Richard Nock Cheng Soon Ong Zhan Shi Christian J. Walder AAML 28 16 0 08 Jun 2018
Generalizing to Unseen Domains via Adversarial Data Augmentation Riccardo Volpi Hongseok Namkoong Ozan Sener John C. Duchi Vittorio Murino Silvio Savarese OOD 41 768 0 30 May 2018
Local Saddle Point Optimization: A Curvature Exploitation Approach Leonard Adolphs Hadi Daneshmand Aurelien Lucchi Thomas Hofmann 37 107 0 15 May 2018
Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing Jingyi Wang Jun Sun Peixin Zhang Xinyu Wang AAML 21 41 0 14 May 2018
Adversarially Robust Generalization Requires More Data Ludwig Schmidt Shibani Santurkar Dimitris Tsipras Kunal Talwar A. Madry OOD AAML 25 785 0 30 Apr 2018
Towards Fast Computation of Certified Robustness for ReLU Networks Tsui-Wei Weng Huan Zhang Hongge Chen Zhao Song Cho-Jui Hsieh Duane S. Boning Inderjit S. Dhillon Luca Daniel AAML 38 686 0 25 Apr 2018
Semantic Adversarial Deep Learning S. Seshia S. Jha T. Dreossi AAML SILM 27 90 0 19 Apr 2018
Adversarial Defense based on Structure-to-Signal Autoencoders Joachim Folz Sebastián M. Palacio Jörn Hees Damian Borth Andreas Dengel AAML 26 32 0 21 Mar 2018
Adversarial Logit Pairing Harini Kannan Alexey Kurakin Ian Goodfellow AAML 36 625 0 16 Mar 2018
Robust GANs against Dishonest Adversaries Zhi Xu Chengtao Li Stefanie Jegelka AAML 34 3 0 27 Feb 2018
Adversarial vulnerability for any classifier Alhussein Fawzi Hamza Fawzi Omar Fawzi AAML 33 248 0 23 Feb 2018
The Robust Manifold Defense: Adversarial Training using Generative Models A. Jalal Andrew Ilyas C. Daskalakis A. Dimakis AAML 31 174 0 26 Dec 2017
Theoretical limitations of Encoder-Decoder GAN architectures Sanjeev Arora Andrej Risteski Yi Zhang GAN AI4CE 14 15 0 07 Nov 2017
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples Yizhen Wang S. Jha Kamalika Chaudhuri AAML 13 154 0 13 Jun 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 65 2,699 0 19 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 249 1,842 0 03 Feb 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 296 3,113 0 04 Nov 2016
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 180 932 0 21 Oct 2016
Statistics of Robust Optimization: A Generalized Empirical Likelihood Approach John C. Duchi Peter Glynn Hongseok Namkoong 4 318 0 11 Oct 2016
Sample Out-Of-Sample Inference Based on Wasserstein Distance Jose H. Blanchet Yang Kang 34 35 0 04 May 2016