Federated Unlearning: How to Efficiently Erase a Client in FL?

12 July 2022

Papers citing "Federated Unlearning: How to Efficiently Erase a Client in FL?"

22 / 22 papers shown

Title
SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Zhihui Zhao Xiaorong Dong Yimo Ren Jianhua Wang Dan Yu Hongsong Zhu Yongle Chen 82 0 0 24 Feb 2025
Data Duplication: A Novel Multi-Purpose Attack Paradigm in Machine Unlearning Dayong Ye Tainqing Zhu Jiashi Li Kun Gao B. Liu Lefei Zhang Wanlei Zhou Yanmei Zhang AAML MU 80 0 0 28 Jan 2025
Unlearning Clients, Features and Samples in Vertical Federated Learning Ayush K. Varshney Konstantinos Vandikas V. Torra MU 39 1 0 23 Jan 2025
The Transition from Centralized Machine Learning to Federated Learning for Mental Health in Education: A Survey of Current Methods and Future Directions Maryam Ebrahimi Rajeev Sahay Seyyedali Hosseinalipour Bita Akram 44 1 0 20 Jan 2025
Streamlined Federated Unlearning: Unite as One to Be Highly Efficient Lei Zhou Youwen Zhu Qiao Xue Ji Zhang Pengfei Zhang MU 89 1 0 28 Nov 2024
MUNBa: Machine Unlearning via Nash Bargaining Jing Wu Mehrtash Harandi MU 71 3 0 23 Nov 2024
WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models Jinghan Jia Jiancheng Liu Yihua Zhang Parikshit Ram Nathalie Baracaldo Sijia Liu MU 35 2 0 23 Oct 2024
Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning Chongyu Fan Jiancheng Liu Licong Lin Jinghan Jia Ruiqi Zhang Song Mei Sijia Liu MU 43 17 0 09 Oct 2024
Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models Tianqi Chen Shujian Zhang Mingyuan Zhou DiffM 83 3 0 17 Sep 2024
FedQUIT: On-Device Federated Unlearning via a Quasi-Competent Virtual Teacher Alessio Mora Lorenzo Valerio Paolo Bellavista A. Passarella FedML MU 49 2 0 14 Aug 2024
A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks Hengzhu Liu Ping Xiong Tianqing Zhu Philip S. Yu 37 6 0 10 Jun 2024
Unlearning during Learning: An Efficient Federated Machine Unlearning Method Hanlin Gu Gongxi Zhu Jie Zhang Xinyuan Zhao Yuxing Han Lixin Fan Qiang Yang MU 46 7 0 24 May 2024
Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity Hanlin Gu W. Ong Chee Seng Chan Lixin Fan MU 39 7 0 23 May 2024
Privacy-Preserving Federated Unlearning with Certified Client Removal Ziyao Liu Huanyi Ye Yu Jiang Jiyuan Shen Jiale Guo Ivan Tjuawinata Kwok-Yan Lam MU 35 5 0 15 Apr 2024
Threats, Attacks, and Defenses in Machine Unlearning: A Survey Ziyao Liu Huanyi Ye Chen Chen Yongsen Zheng K. Lam AAML MU 35 28 0 20 Mar 2024
Federated Learning Priorities Under the European Union Artificial Intelligence Act Herbert Woisetschläger Alexander Erben Bill Marino Shiqiang Wang Nicholas D. Lane R. Mayer Hans-Arno Jacobsen 28 15 0 05 Feb 2024
Subspace based Federated Unlearning Guang-Ming Li Li Shen Yan Sun Yuejun Hu Han Hu Dacheng Tao MU FedML 28 20 0 24 Feb 2023
Knowledge Unlearning for Mitigating Privacy Risks in Language Models Joel Jang Dongkeun Yoon Sohee Yang Sungmin Cha Moontae Lee Lajanugen Logeswaran Minjoon Seo KELM PILM MU 147 193 0 04 Oct 2022
A Survey of Machine Unlearning Thanh Tam Nguyen T. T. Huynh Phi Le Nguyen Alan Wee-Chung Liew Hongzhi Yin Quoc Viet Hung Nguyen MU 79 222 0 06 Sep 2022
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 290 1,824 0 14 Dec 2020
Clean-Label Backdoor Attacks on Video Recognition Models Shihao Zhao Xingjun Ma Xiang Zheng James Bailey Jingjing Chen Yu-Gang Jiang AAML 198 274 0 06 Mar 2020
Machine Unlearning: Linear Filtration for Logit-based Classifiers Thomas Baumhauer Pascal Schöttle Matthias Zeppelzauer MU 109 130 0 07 Feb 2020