Adversarial Training and Robustness for Multiple Perturbations

30 April 2019

Dan Boneh

Papers citing "Adversarial Training and Robustness for Multiple Perturbations"

50 / 86 papers shown

Title
IM-BERT: Enhancing Robustness of BERT through the Implicit Euler Method Mihyeon Kim Juhyoung Park Youngbin Kim 34 0 0 11 May 2025
Impact of Data Duplication on Deep Neural Network-Based Image Classifiers: Robust vs. Standard Models Alireza Aghabagherloo Aydin Abadi Sumanta Sarkar Vishnu Asutosh Dasu Bart Preneel AAML 54 0 0 01 Apr 2025
Carefully Blending Adversarial Training, Purification, and Aggregation Improves Adversarial Robustness Emanuele Ballarin A. Ansuini Luca Bortolussi AAML 62 0 0 20 Feb 2025
Achievable distributional robustness when the robust risk is only partially identified Julia Kostin Nicola Gnecco Fanny Yang 73 3 0 04 Feb 2025
Adversarial Hubness in Multi-Modal Retrieval Tingwei Zhang Fnu Suya Rishi Jha Collin Zhang Vitaly Shmatikov AAML 83 1 0 18 Dec 2024
Slot: Provenance-Driven APT Detection through Graph Reinforcement Learning Wei Qiao Yebo Feng Teng Li Zijian Zhang Zhengzi Xu Zhuo Ma Yulong Shen 32 0 0 23 Oct 2024
Towards Universal Certified Robustness with Multi-Norm Training Enyi Jiang Gagandeep Singh Gagandeep Singh AAML 60 1 0 03 Oct 2024
Evaluating Model Robustness Using Adaptive Sparse L0 Regularization Weiyou Liu Zhenyang Li Weitong Chen AAML 30 1 0 28 Aug 2024
Catastrophic Overfitting: A Potential Blessing in Disguise Mengnan Zhao Lihe Zhang Yuqiu Kong Baocai Yin AAML 44 1 0 28 Feb 2024
Understanding Deep Learning defenses Against Adversarial Examples Through Visualizations for Dynamic Risk Assessment Xabier Echeberria-Barrio Amaia Gil-Lerchundi Jon Egana-Zubia Raul Orduna Urrutia AAML 24 6 0 12 Feb 2024
RAMP: Boosting Adversarial Robustness Against Multiple $l_p$ Perturbations Enyi Jiang Gagandeep Singh AAML 30 1 0 09 Feb 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance Wenqi Wei Ling Liu 28 16 0 02 Feb 2024
CARE: Ensemble Adversarial Robustness Evaluation Against Adaptive Attackers for Security Applications Hangsheng Zhang Jiqiang Liu Jinsong Dong AAML 21 1 0 20 Jan 2024
Adversarial Training for Physics-Informed Neural Networks Yao Li Shengzhu Shi Zhichang Guo Boying Wu AAML PINN 25 0 0 18 Oct 2023
Adversarial Illusions in Multi-Modal Embeddings Tingwei Zhang Rishi Jha Eugene Bagdasaryan Vitaly Shmatikov AAML 31 8 0 22 Aug 2023
Adversarial Learning in Real-World Fraud Detection: Challenges and Perspectives Daniele Lunghi A. Simitsis O. Caelen Gianluca Bontempi AAML FaML 40 4 0 03 Jul 2023
Group-based Robustness: A General Framework for Customized Robustness in the Real World Weiran Lin Keane Lucas Neo Eyal Lujo Bauer Michael K. Reiter Mahmood Sharif OOD AAML 27 1 0 29 Jun 2023
Enhancing Multiple Reliability Measures via Nuisance-extended Information Bottleneck Jongheon Jeong Sihyun Yu Hankook Lee Jinwoo Shin AAML 44 0 0 24 Mar 2023
Decentralized Adversarial Training over Graphs Ying Cao Elsa Rizk Stefan Vlaski A. H. Sayed AAML 35 1 0 23 Mar 2023
Cyber Vaccine for Deepfake Immunity Ching-Chun Chang H. Nguyen Junichi Yamagishi Isao Echizen 26 6 0 05 Mar 2023
MultiRobustBench: Benchmarking Robustness Against Multiple Attacks Sihui Dai Saeed Mahloujifar Chong Xiang Vikash Sehwag Pin-Yu Chen Prateek Mittal AAML OOD 21 7 0 21 Feb 2023
Phase-shifted Adversarial Training Yeachan Kim Seongyeon Kim Ihyeok Seo Bonggun Shin AAML OOD 24 0 0 12 Jan 2023
Alternating Objectives Generates Stronger PGD-Based Adversarial Attacks Nikolaos Antoniou Efthymios Georgiou Alexandros Potamianos AAML 27 5 0 15 Dec 2022
Deep Fake Detection, Deterrence and Response: Challenges and Opportunities Amin Azmoodeh Ali Dehghantanha 34 2 0 26 Nov 2022
Secure and Trustworthy Artificial Intelligence-Extended Reality (AI-XR) for Metaverses Adnan Qayyum M. A. Butt Hassan Ali Muhammad Usman O. Halabi Ala I. Al-Fuqaha Q. Abbasi Muhammad Ali Imran Junaid Qadir 30 32 0 24 Oct 2022
Towards Generating Adversarial Examples on Mixed-type Data Han Xu Menghai Pan Zhimeng Jiang Huiyuan Chen Xiaoting Li Mahashweta Das Hao Yang AAML SILM 10 0 0 17 Oct 2022
Towards Out-of-Distribution Adversarial Robustness Adam Ibrahim Charles Guille-Escuret Ioannis Mitliagkas Irina Rish David M. Krueger P. Bashivan OOD 31 6 0 06 Oct 2022
Practical Adversarial Attacks on Spatiotemporal Traffic Forecasting Models F. Liu Haowen Liu Wenzhao Jiang OOD 64 33 0 05 Oct 2022
Adaptive Smoothness-weighted Adversarial Training for Multiple Perturbations with Its Stability Analysis Jiancong Xiao Zeyu Qin Yanbo Fan Baoyuan Wu Jue Wang Zhimin Luo AAML 31 7 0 02 Oct 2022
On the interplay of adversarial robustness and architecture components: patches, convolution and attention Francesco Croce Matthias Hein 41 6 0 14 Sep 2022
Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms Ehsan Hallaji R. Razavi-Far M. Saif AAML FedML 21 13 0 05 Jul 2022
Vector Quantisation for Robust Segmentation Ainkaran Santhirasekaram Avinash Kori Mathias Winkler A. Rockall Ben Glocker OOD 22 9 0 05 Jul 2022
DECK: Model Hardening for Defending Pervasive Backdoors Guanhong Tao Yingqi Liu Shuyang Cheng Shengwei An Zhuo Zhang Qiuling Xu Guangyu Shen Xiangyu Zhang AAML 20 7 0 18 Jun 2022
Analysis and Extensions of Adversarial Training for Video Classification K. A. Kinfu René Vidal AAML 27 13 0 16 Jun 2022
(De-)Randomized Smoothing for Decision Stump Ensembles Miklós Z. Horváth Mark Niklas Muller Marc Fischer Martin Vechev 30 3 0 27 May 2022
Robustness through Cognitive Dissociation Mitigation in Contrastive Adversarial Training Adir Rahamim I. Naeh AAML 22 1 0 16 Mar 2022
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training Tu Bui Trung Le Quan Hung Tran He Zhao Dinh Q. Phung AAML OOD 31 42 0 27 Feb 2022
On the Effectiveness of Adversarial Training against Backdoor Attacks Yinghua Gao Dongxian Wu Jingfeng Zhang Guanhao Gan Shutao Xia Gang Niu Masashi Sugiyama AAML 32 22 0 22 Feb 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition Tianyu Pang Min-Bin Lin Xiao Yang Junyi Zhu Shuicheng Yan 27 119 0 21 Feb 2022
Mutual Adversarial Training: Learning together is better than going alone Jiang-Long Liu Chun Pong Lau Hossein Souri S. Feizi Ramalingam Chellappa OOD AAML 35 24 0 09 Dec 2021
Pareto Adversarial Robustness: Balancing Spatial Robustness and Sensitivity-based Robustness Ke Sun Mingjie Li Zhouchen Lin AAML 21 2 0 03 Nov 2021
Generalized Depthwise-Separable Convolutions for Adversarially Robust and Efficient Neural Networks Hassan Dbouk Naresh R Shanbhag AAML 19 7 0 28 Oct 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 35 16 0 20 Sep 2021
Adversarial Robustness for Unsupervised Domain Adaptation Muhammad Awais Fengwei Zhou Hang Xu Lanqing Hong Ping Luo Sung-Ho Bae Zhenguo Li 20 39 0 02 Sep 2021
Enhancing MR Image Segmentation with Realistic Adversarial Data Augmentation C. L. P. Chen C. Qin C. Ouyang Zeju Li Shuo Wang Huaqi Qiu Liang Chen G. Tarroni Wenjia Bai Daniel Rueckert GAN MedIm 59 40 0 07 Aug 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Saeed Mian Navid Kardan M. Shah AAML 26 235 0 01 Aug 2021
Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them Florian Tramèr AAML 27 64 0 24 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 16 4 0 06 Jul 2021
The Values Encoded in Machine Learning Research Abeba Birhane Pratyusha Kalluri Dallas Card William Agnew Ravit Dotan Michelle Bao 25 274 0 29 Jun 2021
The Care Label Concept: A Certification Suite for Trustworthy and Resource-Aware Machine Learning K. Morik Helena Kotthaus Lukas Heppe Danny Heinrich Raphael Fischer Andrea Pauly Nico Piatkowski 23 4 0 01 Jun 2021