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Adversarial Robustness through Local Linearization

4 July 2019

Krishnamurthy Dvijotham

Papers citing "Adversarial Robustness through Local Linearization"

50 / 126 papers shown

Title
AdvRush: Searching for Adversarially Robust Neural Architectures J. Mok Byunggook Na Hyeokjun Choe Sungroh Yoon OOD AAML 85 45 0 03 Aug 2021
Adversarial Examples in Multi-Layer Random ReLU Networks Peter L. Bartlett Sébastien Bubeck Yeshwanth Cherapanamjeri AAML GAN 74 29 0 23 Jun 2021
Attacking Adversarial Attacks as A Defense Boxi Wu Heng Pan Li Shen Jindong Gu Shuai Zhao Zhifeng Li Deng Cai Xiaofei He Wei Liu AAML 93 33 0 09 Jun 2021
Exploring Memorization in Adversarial Training Yinpeng Dong Ke Xu Xiao Yang Tianyu Pang Zhijie Deng Hang Su Jun Zhu TDI 58 74 0 03 Jun 2021
NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels Jingfeng Zhang Xilie Xu Bo Han Tongliang Liu Gang Niu Li-zhen Cui Masashi Sugiyama NoLa AAML 87 9 0 31 May 2021
LAFEAT: Piercing Through Adversarial Defenses with Latent Features Yunrui Yu Xitong Gao Chengzhong Xu AAML FedML 91 46 0 19 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 105 67 0 09 Apr 2021
A single gradient step finds adversarial examples on random two-layers neural networks Sébastien Bubeck Yeshwanth Cherapanamjeri Gauthier Gidel Rémi Tachet des Combes MLT 79 28 0 08 Apr 2021
Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation Jungbeom Lee Eunji Kim Sungroh Yoon 85 229 0 16 Mar 2021
Consistency Regularization for Adversarial Robustness Jihoon Tack Sihyun Yu Jongheon Jeong Minseon Kim Sung Ju Hwang Jinwoo Shin AAML 111 61 0 08 Mar 2021
Fixing Data Augmentation to Improve Adversarial Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 121 276 0 02 Mar 2021
Smoothness Analysis of Adversarial Training Sekitoshi Kanai Masanori Yamada Hiroshi Takahashi Yuki Yamanaka Yasutoshi Ida AAML 95 6 0 02 Mar 2021
Explaining Adversarial Vulnerability with a Data Sparsity Hypothesis Mahsa Paknezhad Cuong Phuc Ngo Amadeus Aristo Winarto Alistair Cheong Beh Chuen Yang Wu Jiayang Lee Hwee Kuan OOD AAML 74 9 0 01 Mar 2021
Globally-Robust Neural Networks Klas Leino Zifan Wang Matt Fredrikson AAML OOD 162 131 0 16 Feb 2021
Recent Advances in Adversarial Training for Adversarial Robustness Tao Bai Jinqi Luo Jun Zhao Bihan Wen Qian Wang AAML 196 496 0 02 Feb 2021
Understanding and Increasing Efficiency of Frank-Wolfe Adversarial Training Theodoros Tsiligkaridis Jay Roberts AAML 206 11 0 22 Dec 2020
Open Problems in Cooperative AI Allan Dafoe Edward Hughes Yoram Bachrach Tantum Collins Kevin R. McKee Joel Z Leibo Kate Larson T. Graepel 121 203 0 15 Dec 2020
Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses Gaurang Sriramanan Sravanti Addepalli Arya Baburaj R. Venkatesh Babu AAML 82 95 0 30 Nov 2020
A Study on the Uncertainty of Convolutional Layers in Deep Neural Networks Hao Shen Sihong Chen Ran Wang 70 5 0 27 Nov 2020
Learnable Boundary Guided Adversarial Training Jiequan Cui Shu Liu Liwei Wang Jiaya Jia OOD AAML 113 132 0 23 Nov 2020
Towards Understanding the Regularization of Adversarial Robustness on Neural Networks Yuxin Wen Shuai Li Kui Jia AAML 72 24 0 15 Nov 2020
Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks Huimin Zeng Chen Zhu Tom Goldstein Furong Huang AAML 72 18 0 24 Oct 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 361 707 0 19 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 121 48 0 19 Oct 2020
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples Sven Gowal Chongli Qin J. Uesato Timothy A. Mann Pushmeet Kohli AAML 73 331 0 07 Oct 2020
Geometry-aware Instance-reweighted Adversarial Training Jingfeng Zhang Jianing Zhu Gang Niu Bo Han Masashi Sugiyama Mohan Kankanhalli AAML 103 279 0 05 Oct 2020
Do Wider Neural Networks Really Help Adversarial Robustness? Boxi Wu Jinghui Chen Deng Cai Xiaofei He Quanquan Gu AAML 110 95 0 03 Oct 2020
Efficient Robust Training via Backward Smoothing Jinghui Chen Yu Cheng Zhe Gan Quanquan Gu Jingjing Liu AAML 83 40 0 03 Oct 2020
Bag of Tricks for Adversarial Training Tianyu Pang Xiao Yang Yinpeng Dong Hang Su Jun Zhu AAML 90 270 0 01 Oct 2020
Feature Distillation With Guided Adversarial Contrastive Learning Tao Bai Jinnan Chen Jun Zhao Bihan Wen Xudong Jiang Alex C. Kot AAML 63 9 0 21 Sep 2020
Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness Tuan-Anh Bui Trung Le He Zhao Paul Montague O. deVel Tamas Abraham Dinh Q. Phung AAML FedML 73 11 0 21 Sep 2020
Adversarial Training with Stochastic Weight Average Joong-won Hwang Youngwan Lee Sungchan Oh Yuseok Bae OOD AAML 65 11 0 21 Sep 2020
A Game Theoretic Analysis of Additive Adversarial Attacks and Defenses Ambar Pal René Vidal AAML 106 27 0 14 Sep 2020
Second Order Optimization for Adversarial Robustness and Interpretability Theodoros Tsiligkaridis Jay Roberts AAML 42 8 0 10 Sep 2020
Quantifying the Preferential Direction of the Model Gradient in Adversarial Training With Projected Gradient Descent Ricardo Bigolin Lanfredi Joyce D. Schroeder Tolga Tasdizen 64 12 0 10 Sep 2020
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching Jonas Geiping Liam H. Fowl Wenjie Huang W. Czaja Gavin Taylor Michael Moeller Tom Goldstein AAML 100 222 0 04 Sep 2020
Perceptual Deep Neural Networks: Adversarial Robustness through Input Recreation Danilo Vasconcellos Vargas Bingli Liao Takahiro Kanzaki AAML 45 3 0 02 Sep 2020
Likelihood Landscapes: A Unifying Principle Behind Many Adversarial Defenses Fu-Huei Lin Rohit Mittapalli Prithvijit Chattopadhyay Daniel Bolya Judy Hoffman AAML 63 2 0 25 Aug 2020
Improving Adversarial Robustness by Enforcing Local and Global Compactness Anh-Vu Bui Trung Le He Zhao Paul Montague O. deVel Tamas Abraham Dinh Q. Phung AAML 60 24 0 10 Jul 2020
Understanding and Improving Fast Adversarial Training Maksym Andriushchenko Nicolas Flammarion AAML 106 295 0 06 Jul 2020
Smooth Adversarial Training Cihang Xie Mingxing Tan Boqing Gong Alan Yuille Quoc V. Le OOD 94 154 0 25 Jun 2020
Targeted Adversarial Perturbations for Monocular Depth Prediction A. Wong Safa Cicek Stefano Soatto AAML MDE 62 45 0 12 Jun 2020
Adversarial Feature Desensitization P. Bashivan Reza Bayat Adam Ibrahim Kartik Ahuja Mojtaba Faramarzi Touraj Laleh Blake A. Richards Irina Rish AAML 50 21 0 08 Jun 2020
Second-Order Provable Defenses against Adversarial Attacks Sahil Singla Soheil Feizi AAML 74 60 0 01 Jun 2020
Provable Robust Classification via Learned Smoothed Densities Saeed Saremi R. Srivastava AAML 88 3 0 09 May 2020
GraCIAS: Grassmannian of Corrupted Images for Adversarial Security Ankita Shukla Pavan Turaga Saket Anand AAML 39 1 0 06 May 2020
Bullseye Polytope: A Scalable Clean-Label Poisoning Attack with Improved Transferability H. Aghakhani Dongyu Meng Yu-Xiang Wang Christopher Kruegel Giovanni Vigna AAML 77 104 0 01 May 2020
Adversarial Training for Large Neural Language Models Xiaodong Liu Hao Cheng Pengcheng He Weizhu Chen Yu Wang Hoifung Poon Jianfeng Gao AAML 94 186 0 20 Apr 2020
Approximate Manifold Defense Against Multiple Adversarial Perturbations Jay Nandy Wynne Hsu Mong Li Lee AAML 65 12 0 05 Apr 2020
Toward Adversarial Robustness via Semi-supervised Robust Training Yiming Li Baoyuan Wu Yan Feng Yanbo Fan Yong Jiang Zhifeng Li Shutao Xia AAML 121 13 0 16 Mar 2020