FAT: Federated Adversarial Training

3 December 2020

Papers citing "FAT: Federated Adversarial Training"

21 / 21 papers shown

Title
Central limit theorems for vector-valued composite functionals with smoothing and applications Huhui Chen Darinka Dentcheva Yang Lin Gregory J. Stock 48 3 0 26 Dec 2024
Adversarial Training: A Survey Mengnan Zhao Lihe Zhang Jingwen Ye Huchuan Lu Baocai Yin Xinchao Wang AAML 28 0 0 19 Oct 2024
FedProphet: Memory-Efficient Federated Adversarial Training via Robust and Consistent Cascade Learning Minxue Tang Yitu Wang Jingyang Zhang Louis DiValentin Aolin Ding Amin Hass Yiran Chen Hai "Helen" Li FedML AAML 19 0 0 12 Sep 2024
Logit Calibration and Feature Contrast for Robust Federated Learning on Non-IID Data Yu Qiao Chaoning Zhang Apurba Adhikary Choong Seon Hong FedML 33 7 0 10 Apr 2024
Towards Robust Federated Learning via Logits Calibration on Non-IID Data Yu Qiao Apurba Adhikary Chaoning Zhang Choong Seon Hong FedML 37 8 0 05 Mar 2024
Adversarial Robustness Unhardening via Backdoor Attacks in Federated Learning Taejin Kim Jiarui Li Shubhranshu Singh Nikhil Madaan Carlee Joe-Wong FedML 12 1 0 17 Oct 2023
Improving Machine Learning Robustness via Adversarial Training Long Dang T. Hapuarachchi Kaiqi Xiong Jing Lin OOD AAML 33 2 0 22 Sep 2023
Secure Federated Learning against Model Poisoning Attacks via Client Filtering D. Yaldiz Tuo Zhang Salman Avestimehr AAML FedML 16 13 0 31 Mar 2023
Combating Exacerbated Heterogeneity for Robust Models in Federated Learning Jianing Zhu Jiangchao Yao Tongliang Liu Quanming Yao Jianliang Xu Bo Han FedML 38 5 0 01 Mar 2023
Delving into the Adversarial Robustness of Federated Learning Jie M. Zhang Bo-wen Li Chen Chen Lingjuan Lyu Shuang Wu Shouhong Ding Chao Wu FedML 35 34 0 19 Feb 2023
Robust Learning Protocol for Federated Tumor Segmentation Challenge Ambrish Rawat Giulio Zizzo S. Kadhe J. Epperlein S. Braghin FedML 19 3 0 16 Dec 2022
Characterizing Internal Evasion Attacks in Federated Learning Taejin Kim Shubhranshu Singh Nikhil Madaan Carlee Joe-Wong FedML 26 9 0 17 Sep 2022
FADE: Enabling Federated Adversarial Training on Heterogeneous Resource-Constrained Edge Devices Minxue Tang Jianyi Zhang Mingyuan Ma Louis DiValentin Aolin Ding Amin Hassanzadeh H. Li Yiran Chen FedML 13 0 0 08 Sep 2022
Federated Adversarial Learning: A Framework with Convergence Analysis Xiaoxiao Li Zhao-quan Song Jiaming Yang FedML 27 19 0 07 Aug 2022
Certified Robustness in Federated Learning Motasem Alfarra Juan C. Pérez Egor Shulgin Peter Richtárik Bernard Ghanem AAML FedML 18 7 0 06 Jun 2022
Federated Adversarial Training with Transformers Ahmed Aldahdooh W. Hamidouche Olivier Déforges FedML ViT 20 2 0 05 Jun 2022
Federated Robustness Propagation: Sharing Robustness in Heterogeneous Federated Learning Junyuan Hong Haotao Wang Zhangyang Wang Jiayu Zhou FedML 21 16 0 18 Jun 2021
Adversarial training in communication constrained federated learning Devansh Shah Parijat Dube Supriyo Chakraborty Ashish Verma FedML 19 34 0 01 Mar 2021
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 183 355 0 07 Dec 2020
Adversarial Robustness through Bias Variance Decomposition: A New Perspective for Federated Learning Yao Zhou Jun Wu Haixun Wang Jingrui He AAML FedML 23 26 0 18 Sep 2020
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 261 3,109 0 04 Nov 2016