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Forget-SVGD: Particle-Based Bayesian Federated Unlearning

Forget-SVGD: Particle-Based Bayesian Federated Unlearning

23 November 2021
J. Gong
Osvaldo Simeone
Rahif Kassab
Joonhyuk Kang
    FedML
    MU
ArXivPDFHTML

Papers citing "Forget-SVGD: Particle-Based Bayesian Federated Unlearning"

14 / 14 papers shown
Title
Federated Unlearning Model Recovery in Data with Skewed Label
  Distributions
Federated Unlearning Model Recovery in Data with Skewed Label Distributions
Xinrui Yu
Wenbin Pei
Bing Xue
Qiang Zhang
FedML
MU
84
1
0
18 Dec 2024
Vertical Federated Unlearning via Backdoor Certification
Vertical Federated Unlearning via Backdoor Certification
Mengde Han
Tianqing Zhu
Lefeng Zhang
Huan Huo
Wanlei Zhou
FedML
MU
74
2
0
16 Dec 2024
Streamlined Federated Unlearning: Unite as One to Be Highly Efficient
Lei Zhou
Youwen Zhu
Qiao Xue
Ji Zhang
Pengfei Zhang
MU
94
1
0
28 Nov 2024
A Review on Machine Unlearning
Haibo Zhang
Toru Nakamura
Takamasa Isohara
Kouichi Sakurai
AILaw
PILM
MU
99
47
0
18 Nov 2024
A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks
A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks
Hengzhu Liu
Ping Xiong
Tianqing Zhu
Philip S. Yu
47
6
0
10 Jun 2024
Federated Unlearning: A Survey on Methods, Design Guidelines, and
  Evaluation Metrics
Federated Unlearning: A Survey on Methods, Design Guidelines, and Evaluation Metrics
Nicolò Romandini
Alessio Mora
Carlo Mazzocca
R. Montanari
Paolo Bellavista
FedML
MU
64
22
0
10 Jan 2024
A Survey on Federated Unlearning: Challenges, Methods, and Future
  Directions
A Survey on Federated Unlearning: Challenges, Methods, and Future Directions
Ziyao Liu
Yu Jiang
Jiyuan Shen
Minyi Peng
Kwok-Yan Lam
Xingliang Yuan
Xiaoning Liu
MU
43
46
0
31 Oct 2023
Machine Unlearning: A Survey
Machine Unlearning: A Survey
Heng Xu
Tianqing Zhu
Lefeng Zhang
Wanlei Zhou
Philip S. Yu
MU
41
19
0
06 Jun 2023
On Knowledge Editing in Federated Learning: Perspectives, Challenges,
  and Future Directions
On Knowledge Editing in Federated Learning: Perspectives, Challenges, and Future Directions
Leijie Wu
Song Guo
Junxiao Wang
Zicong Hong
Jie Zhang
Jingren Zhou
KELM
52
4
0
02 Jun 2023
Exploring the Landscape of Machine Unlearning: A Comprehensive Survey
  and Taxonomy
Exploring the Landscape of Machine Unlearning: A Comprehensive Survey and Taxonomy
T. Shaik
Xiaohui Tao
Haoran Xie
Lin Li
Xiaofeng Zhu
Qingyuan Li
MU
47
25
0
10 May 2023
SAFE: Machine Unlearning With Shard Graphs
SAFE: Machine Unlearning With Shard Graphs
Yonatan Dukler
Benjamin Bowman
Alessandro Achille
Aditya Golatkar
A. Swaminathan
Stefano Soatto
MU
26
22
0
25 Apr 2023
Get Rid Of Your Trail: Remotely Erasing Backdoors in Federated Learning
Get Rid Of Your Trail: Remotely Erasing Backdoors in Federated Learning
Manaar Alam
Hithem Lamri
Michail Maniatakos
FedML
AAML
MU
30
14
0
20 Apr 2023
SIFU: Sequential Informed Federated Unlearning for Efficient and
  Provable Client Unlearning in Federated Optimization
SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization
Yann Fraboni
Martin Van Waerebeke
Kevin Scaman
Richard Vidal
Laetitia Kameni
Marco Lorenzi
FedML
MU
15
14
0
21 Nov 2022
Compressed Particle-Based Federated Bayesian Learning and Unlearning
Compressed Particle-Based Federated Bayesian Learning and Unlearning
J. Gong
Osvaldo Simeone
Joonhyuk Kang
FedML
50
10
0
14 Sep 2022
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