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
Cross-Domain Few-Shot Classification via Adversarial Task Augmentation Haoqing Wang Zhihong Deng 32 120 0 29 Apr 2021
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization Siqi Zhang Junchi Yang Cristóbal Guzmán Negar Kiyavash Niao He 33 61 0 29 Mar 2021
Robust Models Are More Interpretable Because Attributions Look Normal Zifan Wang Matt Fredrikson Anupam Datta OOD FAtt 35 25 0 20 Mar 2021
Dynamic Efficient Adversarial Training Guided by Gradient Magnitude Fu Lee Wang Yanghao Zhang Yanbin Zheng Wenjie Ruan 28 1 0 04 Mar 2021
Domain Generalization: A Survey Kaiyang Zhou Ziwei Liu Yu Qiao Tao Xiang Chen Change Loy OOD AI4CE 75 982 0 03 Mar 2021
A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness Jacob D. Abernethy Pranjal Awasthi Satyen Kale AAML 27 6 0 01 Mar 2021
Adversarially Robust Kernel Smoothing Jia-Jie Zhu Christina Kouridi Yassine Nemmour Bernhard Schölkopf 28 7 0 16 Feb 2021
Mixed Nash Equilibria in the Adversarial Examples Game Laurent Meunier M. Scetbon Rafael Pinot Jamal Atif Y. Chevaleyre AAML 23 29 0 13 Feb 2021
Generalization Bounds for Meta-Learning via PAC-Bayes and Uniform Stability Alec Farid Anirudha Majumdar 27 34 0 12 Feb 2021
Fast Training of Provably Robust Neural Networks by SingleProp Akhilan Boopathy Tsui-Wei Weng Sijia Liu Pin-Yu Chen Gaoyuan Zhang Luca Daniel AAML 11 7 0 01 Feb 2021
Increasing the Confidence of Deep Neural Networks by Coverage Analysis Giulio Rossolini Alessandro Biondi Giorgio Buttazzo AAML 26 13 0 28 Jan 2021
DiPSeN: Differentially Private Self-normalizing Neural Networks For Adversarial Robustness in Federated Learning Olakunle Ibitoye M. O. Shafiq Ashraf Matrawy FedML 28 18 0 08 Jan 2021
Why do classifier accuracies show linear trends under distribution shift? Horia Mania S. Sra OOD 37 19 0 31 Dec 2020
Understanding and Increasing Efficiency of Frank-Wolfe Adversarial Training Theodoros Tsiligkaridis Jay Roberts AAML 22 11 0 22 Dec 2020
Unbiased Gradient Estimation for Distributionally Robust Learning Soumyadip Ghosh M. Squillante OOD 26 7 0 22 Dec 2020
Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints X. Li Xiangrui Li Deng Pan D. Zhu AAML 21 17 0 14 Dec 2020
Generating Out of Distribution Adversarial Attack using Latent Space Poisoning Ujjwal Upadhyay Prerana Mukherjee 39 7 0 09 Dec 2020
FairBatch: Batch Selection for Model Fairness Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh VLM 14 128 0 03 Dec 2020
A Study on the Uncertainty of Convolutional Layers in Deep Neural Networks Hao Shen Sihong Chen Ran Wang 30 5 0 27 Nov 2020
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems N. Sohoni Jared A. Dunnmon Geoffrey Angus Albert Gu Christopher Ré 30 242 0 25 Nov 2020
Adversarially Robust Classification based on GLRT Bhagyashree Puranik Upamanyu Madhow Ramtin Pedarsani VLM AAML 23 4 0 16 Nov 2020
Statistical Inference for Maximin Effects: Identifying Stable Associations across Multiple Studies Zijian Guo 28 17 0 15 Nov 2020
Robust and Stable Black Box Explanations Himabindu Lakkaraju Nino Arsov Osbert Bastani AAML FAtt 24 84 0 12 Nov 2020
Domain adaptation under structural causal models Yuansi Chen Peter Buhlmann CML OOD AI4CE 36 38 0 29 Oct 2020
Evaluating Model Robustness and Stability to Dataset Shift Adarsh Subbaswamy R. Adams Suchi Saria OOD 26 9 0 28 Oct 2020
Coping with Label Shift via Distributionally Robust Optimisation J.N. Zhang A. Menon Andreas Veit Srinadh Bhojanapalli Sanjiv Kumar S. Sra OOD 24 70 0 23 Oct 2020
Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness Long Zhao Ting Liu Xi Peng Dimitris N. Metaxas OOD AAML 27 165 0 15 Oct 2020
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks Keyulu Xu Mozhi Zhang Jingling Li S. Du Ken-ichi Kawarabayashi Stefanie Jegelka MLT 25 306 0 24 Sep 2020
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Bo-wen Li AAML 33 128 0 09 Sep 2020
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective G. R. Machado Eugênio Silva R. Goldschmidt AAML 33 157 0 08 Sep 2020
Rethinking Non-idealities in Memristive Crossbars for Adversarial Robustness in Neural Networks Abhiroop Bhattacharjee Priyadarshini Panda AAML 28 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 48 0 24 Aug 2020
Adversarial Training and Provable Robustness: A Tale of Two Objectives Jiameng Fan Wenchao Li AAML 23 20 0 13 Aug 2020
Robust Validation: Confident Predictions Even When Distributions Shift Maxime Cauchois Suyash Gupta Alnur Ali John C. Duchi OOD 24 90 0 10 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 27 73 0 07 Aug 2020
Distributionally Robust Losses for Latent Covariate Mixtures John C. Duchi Tatsunori Hashimoto Hongseok Namkoong 18 79 0 28 Jul 2020
Robust Machine Learning via Privacy/Rate-Distortion Theory Ye Wang Shuchin Aeron Adnan Siraj Rakin T. Koike-Akino P. Moulin OOD 22 6 0 22 Jul 2020
Counterfactual Data Augmentation using Locally Factored Dynamics Silviu Pitis Elliot Creager Animesh Garg BDL OffRL 26 85 0 06 Jul 2020
Measuring Robustness to Natural Distribution Shifts in Image Classification Rohan Taori Achal Dave Vaishaal Shankar Nicholas Carlini Benjamin Recht Ludwig Schmidt OOD 39 536 0 01 Jul 2020
A Le Cam Type Bound for Adversarial Learning and Applications Qiuling Xu Kevin Bello Jean Honorio AAML 23 1 0 01 Jul 2020
Counterexample-Guided Learning of Monotonic Neural Networks Aishwarya Sivaraman G. Farnadi T. Millstein Mathias Niepert 24 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 24 81 0 15 Jun 2020
Defensive Approximation: Securing CNNs using Approximate Computing Amira Guesmi Ihsen Alouani Khaled N. Khasawneh M. Baklouti T. Frikha Mohamed Abid Nael B. Abu-Ghazaleh AAML 19 37 0 13 Jun 2020
Risk Variance Penalization Chuanlong Xie Haotian Ye Fei Chen Yue Liu Rui Sun Zhenguo Li 53 33 0 13 Jun 2020
Probably Approximately Correct Constrained Learning Luiz F. O. Chamon Alejandro Ribeiro 22 38 0 09 Jun 2020
A Stochastic Subgradient Method for Distributionally Robust Non-Convex Learning Mert Gurbuzbalaban A. Ruszczynski Landi Zhu 26 9 0 08 Jun 2020
Stable Adversarial Learning under Distributional Shifts Jiashuo Liu Zheyan Shen Peng Cui Linjun Zhou Kun Kuang Yangqiu Song Yishi Lin OOD 27 30 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
Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers S. Melacci Gabriele Ciravegna Angelo Sotgiu Ambra Demontis Battista Biggio Marco Gori Fabio Roli 11 14 0 06 Jun 2020
Principled learning method for Wasserstein distributionally robust optimization with local perturbations Yongchan Kwon Wonyoung Hedge Kim Joong-Ho Won M. Paik 22 12 0 05 Jun 2020