Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Too Much Accuracy

16 June 2019

Papers citing "Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Too Much Accuracy"

22 / 22 papers shown

Title
DYNAMITE: Dynamic Defense Selection for Enhancing Machine Learning-based Intrusion Detection Against Adversarial Attacks Jing Chen Onat Gungor Zhengli Shang Elvin Li T. Rosing AAML 30 0 0 17 Apr 2025
Mixing Classifiers to Alleviate the Accuracy-Robustness Trade-Off Yatong Bai Brendon G. Anderson Somayeh Sojoudi AAML 19 2 0 26 Nov 2023
Generalist: Decoupling Natural and Robust Generalization Hongjun Wang Yisen Wang OOD AAML 22 14 0 24 Mar 2023
Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing Yatong Bai Brendon G. Anderson Aerin Kim Somayeh Sojoudi AAML 19 18 0 29 Jan 2023
Data-free Defense of Black Box Models Against Adversarial Attacks Gaurav Kumar Nayak Inder Khatri Ruchit Rawal Anirban Chakraborty AAML 14 1 0 03 Nov 2022
AugRmixAT: A Data Processing and Training Method for Improving Multiple Robustness and Generalization Performance Xiaoliang Liu S. Furao Jian Zhao Changhai Nie AAML 11 1 0 21 Jul 2022
Learn2Weight: Parameter Adaptation against Similar-domain Adversarial Attacks Siddhartha Datta AAML 25 4 0 15 May 2022
Universum-inspired Supervised Contrastive Learning Aiyang Han Chuanxing Geng Songcan Chen SSL 21 3 0 22 Apr 2022
Modality-Balanced Embedding for Video Retrieval Xun Wang Bingqing Ke Xuanping Li Fangyu Liu Mingyu Zhang Xiao Liang Qi-En Xiao Cheng Luo Yue Yu 16 9 0 18 Apr 2022
Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning Mathias Lechner Alexander Amini Daniela Rus T. Henzinger AAML 16 9 0 15 Apr 2022
Interpolated Joint Space Adversarial Training for Robust and Generalizable Defenses Chun Pong Lau Jiang-Long Liu Hossein Souri Wei-An Lin S. Feizi Ramalingam Chellappa AAML 19 12 0 12 Dec 2021
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning Yangsibo Huang Samyak Gupta Zhao-quan Song Kai Li Sanjeev Arora FedML AAML SILM 12 269 0 30 Nov 2021
Towards Understanding the Data Dependency of Mixup-style Training Muthuraman Chidambaram Xiang Wang Yuzheng Hu Chenwei Wu Rong Ge UQCV 28 24 0 14 Oct 2021
Survey: Image Mixing and Deleting for Data Augmentation Humza Naveed Saeed Anwar Munawar Hayat Kashif Javed Ajmal Mian 26 76 0 13 Jun 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 13 65 0 09 Apr 2021
Adversarially Optimized Mixup for Robust Classification Jason Bunk Srinjoy Chattopadhyay B. S. Manjunath S. Chandrasekaran AAML 11 8 0 22 Mar 2021
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 19 48 0 19 Oct 2020
Addressing Neural Network Robustness with Mixup and Targeted Labeling Adversarial Training Alfred Laugros A. Caplier Matthieu Ospici AAML 14 19 0 19 Aug 2020
Stylized Adversarial Defense Muzammal Naseer Salman Khan Munawar Hayat F. Khan Fatih Porikli GAN AAML 13 16 0 29 Jul 2020
Neural Architecture Search with Reinforcement Learning Barret Zoph Quoc V. Le 264 5,319 0 05 Nov 2016
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 256 3,108 0 04 Nov 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 250 5,830 0 08 Jul 2016