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The Right to be Forgotten in Federated Learning: An Efficient
  Realization with Rapid Retraining

The Right to be Forgotten in Federated Learning: An Efficient Realization with Rapid Retraining

14 March 2022
Yi Liu
Lei Xu
Xingliang Yuan
Cong Wang
Bo Li
    MU
ArXivPDFHTML

Papers citing "The Right to be Forgotten in Federated Learning: An Efficient Realization with Rapid Retraining"

27 / 27 papers shown
Title
PRUNE: A Patching Based Repair Framework for Certifiable Unlearning of Neural Networks
PRUNE: A Patching Based Repair Framework for Certifiable Unlearning of Neural Networks
Xuzhao Li
Jingyi Wang
Xiaohan Yuan
Peixin Zhang
Zhan Qin
Peng Kuang
Kui Ren
AAML
MU
52
0
0
10 May 2025
FedMobile: Enabling Knowledge Contribution-aware Multi-modal Federated Learning with Incomplete Modalities
FedMobile: Enabling Knowledge Contribution-aware Multi-modal Federated Learning with Incomplete Modalities
Yi Liu
Cong Wang
Xingliang Yuan
44
1
0
20 Feb 2025
Ten Challenging Problems in Federated Foundation Models
Ten Challenging Problems in Federated Foundation Models
Tao Fan
Hanlin Gu
Xuemei Cao
Chee Seng Chan
Qian Chen
...
Y. Zhang
Xiaojin Zhang
Zhenzhe Zheng
Lixin Fan
Qiang Yang
FedML
89
4
0
14 Feb 2025
Streamlined Federated Unlearning: Unite as One to Be Highly Efficient
Lei Zhou
Youwen Zhu
Qiao Xue
Ji Zhang
Pengfei Zhang
MU
92
1
0
28 Nov 2024
MUNBa: Machine Unlearning via Nash Bargaining
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
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
40
2
0
23 Oct 2024
Efficient Federated Unlearning under Plausible Deniability
Efficient Federated Unlearning under Plausible Deniability
Ayush K. Varshney
V. Torra
MU
40
3
0
13 Oct 2024
Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning
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
FedQUIT: On-Device Federated Unlearning via a Quasi-Competent Virtual Teacher
FedQUIT: On-Device Federated Unlearning via a Quasi-Competent Virtual Teacher
Alessio Mora
Lorenzo Valerio
Paolo Bellavista
A. Passarella
FedML
MU
57
2
0
14 Aug 2024
MU-Bench: A Multitask Multimodal Benchmark for Machine Unlearning
MU-Bench: A Multitask Multimodal Benchmark for Machine Unlearning
Jiali Cheng
Hadi Amiri
BDL
45
3
0
21 Jun 2024
Label Smoothing Improves Machine Unlearning
Label Smoothing Improves Machine Unlearning
Zonglin Di
Zhaowei Zhu
Jinghan Jia
Jiancheng Liu
Zafar Takhirov
Bo Jiang
Yuanshun Yao
Sijia Liu
Yang Liu
40
2
0
11 Jun 2024
Towards Federated Domain Unlearning: Verification Methodologies and
  Challenges
Towards Federated Domain Unlearning: Verification Methodologies and Challenges
Kahou Tam
Kewei Xu
Li Li
Huazhu Fu
MU
43
1
0
05 Jun 2024
Unlearning during Learning: An Efficient Federated Machine Unlearning Method
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
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
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
Communication-Efficient Large-Scale Distributed Deep Learning: A
  Comprehensive Survey
Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey
Feng Liang
Zhen Zhang
Haifeng Lu
Victor C. M. Leung
Yanyi Guo
Xiping Hu
GNN
37
6
0
09 Apr 2024
Threats, Attacks, and Defenses in Machine Unlearning: A Survey
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
Fed-CVLC: Compressing Federated Learning Communications with
  Variable-Length Codes
Fed-CVLC: Compressing Federated Learning Communications with Variable-Length Codes
Xiaoxin Su
Yipeng Zhou
Laizhong Cui
John C. S. Lui
Jiangchuan Liu
FedML
39
1
0
06 Feb 2024
Machine unlearning through fine-grained model parameters perturbation
Machine unlearning through fine-grained model parameters perturbation
Zhiwei Zuo
Zhuo Tang
KenLi Li
Anwitaman Datta
AAML
MU
26
0
0
09 Jan 2024
SecureCut: Federated Gradient Boosting Decision Trees with Efficient
  Machine Unlearning
SecureCut: Federated Gradient Boosting Decision Trees with Efficient Machine Unlearning
Jian Zhang
Bowen Li Jie Li
Chentao Wu
MU
44
3
0
22 Nov 2023
MultiDelete for Multimodal Machine Unlearning
MultiDelete for Multimodal Machine Unlearning
Jiali Cheng
Hadi Amiri
MU
44
7
0
18 Nov 2023
GNNDelete: A General Strategy for Unlearning in Graph Neural Networks
GNNDelete: A General Strategy for Unlearning in Graph Neural Networks
Jiali Cheng
George Dasoulas
Huan He
Chirag Agarwal
Marinka Zitnik
MU
42
36
0
26 Feb 2023
Federated Unlearning: How to Efficiently Erase a Client in FL?
Federated Unlearning: How to Efficiently Erase a Client in FL?
Anisa Halimi
S. Kadhe
Ambrish Rawat
Nathalie Baracaldo
MU
22
122
0
12 Jul 2022
Efficient Attribute Unlearning: Towards Selective Removal of Input
  Attributes from Feature Representations
Efficient Attribute Unlearning: Towards Selective Removal of Input Attributes from Feature Representations
Tao Guo
Song Guo
Jiewei Zhang
Wenchao Xu
Junxiao Wang
MU
27
17
0
27 Feb 2022
Device Sampling for Heterogeneous Federated Learning: Theory,
  Algorithms, and Implementation
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation
Su Wang
Mengyuan Lee
Seyyedali Hosseinalipour
Roberto Morabito
M. Chiang
Christopher G. Brinton
FedML
82
110
0
04 Jan 2021
Poisoning Semi-supervised Federated Learning via Unlabeled Data: Attacks
  and Defenses
Poisoning Semi-supervised Federated Learning via Unlabeled Data: Attacks and Defenses
Yi Liu
Xingliang Yuan
Ruihui Zhao
Cong Wang
Dusit Niyato
Yefeng Zheng
33
5
0
08 Dec 2020
Machine Unlearning: Linear Filtration for Logit-based Classifiers
Machine Unlearning: Linear Filtration for Logit-based Classifiers
Thomas Baumhauer
Pascal Schöttle
Matthias Zeppelzauer
MU
114
130
0
07 Feb 2020
1