Geometry-aware Instance-reweighted Adversarial Training

5 October 2020

Bo Han

Papers citing "Geometry-aware Instance-reweighted Adversarial Training"

32 / 182 papers shown

Title
Which Samples Should be Learned First: Easy or Hard? Xiaoling Zhou Ou Wu 19 17 0 11 Oct 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Hanxun Huang Yisen Wang S. Erfani Quanquan Gu James Bailey Xingjun Ma AAML TPM 44 100 0 07 Oct 2021
Federated Learning of Molecular Properties with Graph Neural Networks in a Heterogeneous Setting Wei-wei Zhu Jiebo Luo Andrew D. White FedML 20 32 0 15 Sep 2021
Delving into Deep Image Prior for Adversarial Defense: A Novel Reconstruction-based Defense Framework Li Ding Yongwei Wang Xin Ding Kaiwen Yuan Ping Wang Hua Huang Z. J. Wang AAML 21 7 0 31 Jul 2021
ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients Alessandro Cappelli Julien Launay Laurent Meunier Ruben Ohana Iacopo Poli AAML 10 4 0 06 Jul 2021
Local Reweighting for Adversarial Training Ruize Gao Feng Liu Kaiwen Zhou Gang Niu Bo Han James Cheng AAML OOD 12 6 0 30 Jun 2021
Probabilistic Margins for Instance Reweighting in Adversarial Training Qizhou Wang Feng Liu Bo Han Tongliang Liu Chen Gong Gang Niu Mingyuan Zhou Masashi Sugiyama AAML 21 61 0 15 Jun 2021
Inverting Adversarially Robust Networks for Image Synthesis Renan A. Rojas-Gomez Raymond A. Yeh Minh Do A. Nguyen 11 4 0 13 Jun 2021
Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm Mingkang Zhu Tianlong Chen Zhangyang Wang AAML 14 20 0 10 Jun 2021
Reliable Adversarial Distillation with Unreliable Teachers Jianing Zhu Jiangchao Yao Bo Han Jingfeng Zhang Tongliang Liu Gang Niu Jingren Zhou Jianliang Xu Hongxia Yang AAML 16 59 0 09 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 19 31 0 09 Jun 2021
Towards the Memorization Effect of Neural Networks in Adversarial Training Han Xu Xiaorui Liu Wentao Wang Wenbiao Ding Zhongqin Wu Zitao Liu Anil K. Jain Jiliang Tang TDI AAML 11 6 0 09 Jun 2021
Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart Tianyu Pang Huishuai Zhang Di He Yinpeng Dong Hang Su Wei Chen Jun Zhu Tie-Yan Liu AAML 8 16 0 31 May 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 15 9 0 31 May 2021
Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks Leo Schwinn René Raab A. Nguyen Dario Zanca Bjoern M. Eskofier AAML 14 58 0 21 May 2021
Evaluating the Robustness of Geometry-Aware Instance-Reweighted Adversarial Training Dorjan Hitaj Giulio Pagnotta I. Masi L. Mancini OOD AAML 16 22 0 02 Mar 2021
Multiplicative Reweighting for Robust Neural Network Optimization Noga Bar Tomer Koren Raja Giryes OOD NoLa 11 9 0 24 Feb 2021
Automated Discovery of Adaptive Attacks on Adversarial Defenses Chengyuan Yao Pavol Bielik Petar Tsankov Martin Vechev AAML 19 24 0 23 Feb 2021
Data Quality Matters For Adversarial Training: An Empirical Study Chengyu Dong Liyuan Liu Jingbo Shang AAML 16 10 0 15 Feb 2021
Guided Interpolation for Adversarial Training Chen Chen Jingfeng Zhang Xilie Xu Tianlei Hu Gang Niu Gang Chen Masashi Sugiyama AAML 16 10 0 15 Feb 2021
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning Yifan Zhang Bryan Hooi Dapeng Hu Jian Liang Jiashi Feng 71 64 0 12 Feb 2021
CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection Hanshu Yan Jingfeng Zhang Gang Niu Jiashi Feng Vincent Y. F. Tan Masashi Sugiyama AAML 16 41 0 10 Feb 2021
Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training Lue Tao Lei Feng Jinfeng Yi Sheng-Jun Huang Songcan Chen AAML 26 71 0 09 Feb 2021
SPADE: A Spectral Method for Black-Box Adversarial Robustness Evaluation Wuxinlin Cheng Chenhui Deng Zhiqiang Zhao Yaohui Cai Zhiru Zhang Zhuo Feng AAML 14 13 0 07 Feb 2021
Understanding the Interaction of Adversarial Training with Noisy Labels Jianing Zhu Jingfeng Zhang Bo Han Tongliang Liu Gang Niu Hongxia Yang Mohan S. Kankanhalli Masashi Sugiyama AAML 14 27 0 06 Feb 2021
With False Friends Like These, Who Can Notice Mistakes? Lue Tao Lei Feng Jinfeng Yi Songcan Chen AAML 13 5 0 29 Dec 2020
Towards Robust Neural Networks via Orthogonal Diversity Kun Fang Qinghua Tao Yingwen Wu Tao Li Jia Cai Feipeng Cai Xiaolin Huang Jie-jin Yang AAML 28 8 0 23 Oct 2020
Maximum Mean Discrepancy Test is Aware of Adversarial Attacks Ruize Gao Feng Liu Jingfeng Zhang Bo Han Tongliang Liu Gang Niu Masashi Sugiyama AAML 11 51 0 22 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 219 676 0 19 Oct 2020
Adversarial Feature Desensitization P. Bashivan Reza Bayat Adam Ibrahim Kartik Ahuja Mojtaba Faramarzi Touraj Laleh Blake A. Richards Irina Rish AAML 6 21 0 08 Jun 2020
Increasing-Margin Adversarial (IMA) Training to Improve Adversarial Robustness of Neural Networks Linhai Ma Liang Liang AAML 18 18 0 19 May 2020
A Closer Look at Accuracy vs. Robustness Yao-Yuan Yang Cyrus Rashtchian Hongyang R. Zhang Ruslan Salakhutdinov Kamalika Chaudhuri OOD 66 26 0 05 Mar 2020