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Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity

Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity

23 May 2024
Hanlin Gu
W. Ong
Chee Seng Chan
Lixin Fan
    MU
ArXivPDFHTML

Papers citing "Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity"

15 / 15 papers shown
Title
ForgetMe: Evaluating Selective Forgetting in Generative Models
ForgetMe: Evaluating Selective Forgetting in Generative Models
Zhenyu Yu
Mohd Yamani Inda Idris
Pei Wang
DiffM
MU
32
0
0
17 Apr 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
73
4
0
14 Feb 2025
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
34
2
0
14 Aug 2024
Machine Unlearning for Image-to-Image Generative Models
Machine Unlearning for Image-to-Image Generative Models
Guihong Li
Hsiang Hsu
Chun-Fu Chen
R. Marculescu
MU
VLM
64
24
0
01 Feb 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
54
22
0
10 Jan 2024
New Job, New Gender? Measuring the Social Bias in Image Generation
  Models
New Job, New Gender? Measuring the Social Bias in Image Generation Models
Wenxuan Wang
Haonan Bai
Jen-tse Huang
Yuxuan Wan
Youliang Yuan
Haoyi Qiu
Nanyun Peng
Michael R. Lyu
34
20
0
01 Jan 2024
Boundary Unlearning
Boundary Unlearning
Min Chen
Weizhuo Gao
Gaoyang Liu
Kai Peng
Chen Wang
MU
101
69
0
21 Mar 2023
Backdoor Attacks and Defenses in Federated Learning: Survey, Challenges
  and Future Research Directions
Backdoor Attacks and Defenses in Federated Learning: Survey, Challenges and Future Research Directions
Thuy-Dung Nguyen
Tuan Nguyen
Phi Le Nguyen
Hieu H. Pham
Khoa D. Doan
Kok-Seng Wong
AAML
FedML
32
55
0
03 Mar 2023
A Survey of Machine Unlearning
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
77
216
0
06 Sep 2022
VeriFi: Towards Verifiable Federated Unlearning
VeriFi: Towards Verifiable Federated Unlearning
Xiangshan Gao
Xingjun Ma
Jingyi Wang
Youcheng Sun
Bo Li
S. Ji
Peng Cheng
Jiming Chen
MU
62
46
0
25 May 2022
Are Your Sensitive Attributes Private? Novel Model Inversion Attribute
  Inference Attacks on Classification Models
Are Your Sensitive Attributes Private? Novel Model Inversion Attribute Inference Attacks on Classification Models
Shagufta Mehnaz
S. V. Dibbo
Ehsanul Kabir
Ninghui Li
E. Bertino
MIACV
27
60
0
23 Jan 2022
Unsupervised Learning of Debiased Representations with Pseudo-Attributes
Unsupervised Learning of Debiased Representations with Pseudo-Attributes
Seonguk Seo
Joon-Young Lee
Bohyung Han
FaML
64
47
0
06 Aug 2021
Unlearnable Examples: Making Personal Data Unexploitable
Unlearnable Examples: Making Personal Data Unexploitable
Hanxun Huang
Xingjun Ma
S. Erfani
James Bailey
Yisen Wang
MIACV
136
189
0
13 Jan 2021
Mixed-Privacy Forgetting in Deep Networks
Mixed-Privacy Forgetting in Deep Networks
Aditya Golatkar
Alessandro Achille
Avinash Ravichandran
M. Polito
Stefano Soatto
CLL
MU
125
158
0
24 Dec 2020
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
294
4,143
0
23 Aug 2019
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