You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle

2 May 2019

Tianyuan Zhang

Papers citing "You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle"

50 / 87 papers shown

Title
Data Selection via Optimal Control for Language Models Yuxian Gu Li Dong Hongning Wang Y. Hao Qingxiu Dong Furu Wei Minlie Huang AI4CE 52 4 0 09 Oct 2024
Exploiting the Layered Intrinsic Dimensionality of Deep Models for Practical Adversarial Training Enes Altinisik Safa Messaoud H. Sencar Hassan Sajjad Sanjay Chawla AAML 45 0 0 27 May 2024
LAMPAT: Low-Rank Adaption for Multilingual Paraphrasing Using Adversarial Training Khoi M. Le Trinh Pham Tho Quan A. Luu 19 7 0 09 Jan 2024
SCAAT: Improving Neural Network Interpretability via Saliency Constrained Adaptive Adversarial Training Rui Xu Wenkang Qin Peixiang Huang Hao Wang Lin Luo FAtt AAML 28 2 0 09 Nov 2023
Robust Mixture-of-Expert Training for Convolutional Neural Networks Yihua Zhang Ruisi Cai Tianlong Chen Guanhua Zhang Huan Zhang Pin-Yu Chen Shiyu Chang Zhangyang Wang Sijia Liu MoE AAML OOD 34 16 0 19 Aug 2023
A Theoretical Perspective on Subnetwork Contributions to Adversarial Robustness Jovon Craig Joshua Andle Theodore S. Nowak S. Y. Sekeh AAML 39 0 0 07 Jul 2023
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses Joana Cabral Costa Tiago Roxo Hugo Manuel Proença Pedro R. M. Inácio AAML 37 49 0 18 May 2023
Beyond Empirical Risk Minimization: Local Structure Preserving Regularization for Improving Adversarial Robustness Wei Wei Jiahuan Zhou Yingying Wu AAML 13 0 0 29 Mar 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min-Bin Lin Weiwei Liu Shuicheng Yan DiffM 21 208 0 09 Feb 2023
On adversarial robustness and the use of Wasserstein ascent-descent dynamics to enforce it Camilo A. Garcia Trillos Nicolas García Trillos 16 5 0 09 Jan 2023
Explainability and Robustness of Deep Visual Classification Models Jindong Gu AAML 39 2 0 03 Jan 2023
Guidance Through Surrogate: Towards a Generic Diagnostic Attack Muzammal Naseer Salman Khan Fatih Porikli F. Khan AAML 20 1 0 30 Dec 2022
The Underlying Correlated Dynamics in Neural Training Rotem Turjeman Tom Berkov I. Cohen Guy Gilboa 19 3 0 18 Dec 2022
Alternating Objectives Generates Stronger PGD-Based Adversarial Attacks Nikolaos Antoniou Efthymios Georgiou Alexandros Potamianos AAML 27 5 0 15 Dec 2022
Adaptive adversarial training method for improving multi-scale GAN based on generalization bound theory Jin-Lin Tang B. Tao Zeyu Gong Zhoupin Yin AI4CE 31 1 0 30 Nov 2022
Rethinking the Number of Shots in Robust Model-Agnostic Meta-Learning Xiaoyue Duan Guoliang Kang Runqi Wang Shumin Han Shenjun Xue Tian Wang Baochang Zhang 24 2 0 28 Nov 2022
Generative Adversarial Training Can Improve Neural Language Models Sajad Movahedi A. Shakery GAN AI4CE 20 2 0 02 Nov 2022
Visual Prompting for Adversarial Robustness Aochuan Chen P. Lorenz Yuguang Yao Pin-Yu Chen Sijia Liu VLM VPVLM 25 32 0 12 Oct 2022
Robust Models are less Over-Confident Julia Grabinski Paul Gavrikov J. Keuper M. Keuper AAML 28 24 0 12 Oct 2022
Saliency Guided Adversarial Training for Learning Generalizable Features with Applications to Medical Imaging Classification System Xin Li Yao Qiang Chengyin Li Sijia Liu D. Zhu OOD MedIm 29 4 0 09 Sep 2022
Adversarial Vulnerability of Temporal Feature Networks for Object Detection Svetlana Pavlitskaya Nikolai Polley Michael Weber J. Marius Zöllner AAML 14 2 0 23 Aug 2022
Masked Spatial-Spectral Autoencoders Are Excellent Hyperspectral Defenders Jiahao Qi Z. Gong Xingyue Liu Kangcheng Bin Chen Chen Yongqiang Li Wei Xue Yu Zhang P. Zhong AAML 34 6 0 16 Jul 2022
RUSH: Robust Contrastive Learning via Randomized Smoothing Yijiang Pang Boyang Liu Jiayu Zhou OOD AAML 19 1 0 11 Jul 2022
Distributed Adversarial Training to Robustify Deep Neural Networks at Scale Gaoyuan Zhang Songtao Lu Yihua Zhang Xiangyi Chen Pin-Yu Chen Quanfu Fan Lee Martie L. Horesh Min-Fong Hong Sijia Liu OOD 24 12 0 13 Jun 2022
Building Robust Ensembles via Margin Boosting Dinghuai Zhang Hongyang R. Zhang Aaron Courville Yoshua Bengio Pradeep Ravikumar A. Suggala AAML UQCV 40 15 0 07 Jun 2022
Defending a Music Recommender Against Hubness-Based Adversarial Attacks Katharina Hoedt A. Flexer Gerhard Widmer AAML 19 3 0 24 May 2022
CE-based white-box adversarial attacks will not work using super-fitting Youhuan Yang Lei Sun Leyu Dai Song Guo Xiuqing Mao Xiaoqin Wang Bayi Xu AAML 24 0 0 04 May 2022
Adversarial Robustness through the Lens of Convolutional Filters Paul Gavrikov J. Keuper 30 15 0 05 Apr 2022
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective Yimeng Zhang Yuguang Yao Jinghan Jia Jinfeng Yi Min-Fong Hong Shiyu Chang Sijia Liu AAML 13 33 0 27 Mar 2022
Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models Ning Ding Yujia Qin Guang Yang Fu Wei Zonghan Yang ... Jianfei Chen Yang Liu Jie Tang Juan Li Maosong Sun 17 196 0 14 Mar 2022
Semi-Implicit Hybrid Gradient Methods with Application to Adversarial Robustness Beomsu Kim Junghoon Seo AAML 20 0 0 21 Feb 2022
Robust Binary Models by Pruning Randomly-initialized Networks Chen Liu Ziqi Zhao Sabine Süsstrunk Mathieu Salzmann TPM AAML MQ 19 4 0 03 Feb 2022
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training Chen Liu Zhichao Huang Mathieu Salzmann Tong Zhang Sabine Süsstrunk AAML 15 13 0 14 Dec 2021
LTD: Low Temperature Distillation for Robust Adversarial Training Erh-Chung Chen Che-Rung Lee AAML 24 26 0 03 Nov 2021
Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks Maksym Yatsura J. H. Metzen Matthias Hein OOD 26 14 0 02 Nov 2021
AugMax: Adversarial Composition of Random Augmentations for Robust Training Haotao Wang Chaowei Xiao Jean Kossaifi Zhiding Yu Anima Anandkumar Zhangyang Wang 19 106 0 26 Oct 2021
TESDA: Transform Enabled Statistical Detection of Attacks in Deep Neural Networks C. Amarnath Aishwarya H. Balwani Kwondo Ma Abhijit Chatterjee AAML 13 3 0 16 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 46 100 0 07 Oct 2021
HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training with Crafted Input Noise Souvik Kundu Massoud Pedram P. Beerel AAML 11 70 0 06 Oct 2021
BulletTrain: Accelerating Robust Neural Network Training via Boundary Example Mining Weizhe Hua Yichi Zhang Chuan Guo Zhiru Zhang G. E. Suh OOD 39 15 0 29 Sep 2021
Improving Gradient-based Adversarial Training for Text Classification by Contrastive Learning and Auto-Encoder Yao Qiu Jinchao Zhang Jie Zhou AAML SILM 27 16 0 14 Sep 2021
On the regularized risk of distributionally robust learning over deep neural networks Camilo A. Garcia Trillos Nicolas García Trillos OOD 37 10 0 13 Sep 2021
TREATED:Towards Universal Defense against Textual Adversarial Attacks Bin Zhu Zhaoquan Gu Le Wang Zhihong Tian AAML 28 8 0 13 Sep 2021
Adversarial Parameter Defense by Multi-Step Risk Minimization Zhiyuan Zhang Ruixuan Luo Xuancheng Ren Qi Su Liangyou Li Xu Sun AAML 23 6 0 07 Sep 2021
A Survey on Data Augmentation for Text Classification Markus Bayer M. Kaufhold Christian A. Reuter 33 334 0 07 Jul 2021
Certification of embedded systems based on Machine Learning: A survey Guillaume Vidot Christophe Gabreau I. Ober Iulian Ober 8 12 0 14 Jun 2021
Concurrent Adversarial Learning for Large-Batch Training Yong Liu Xiangning Chen Minhao Cheng Cho-Jui Hsieh Yang You ODL 28 13 0 01 Jun 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
LAFEAT: Piercing Through Adversarial Defenses with Latent Features Yunrui Yu Xitong Gao Chengzhong Xu AAML FedML 25 44 0 19 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 27 65 0 09 Apr 2021