Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2202.03460
Cited By
Deletion Inference, Reconstruction, and Compliance in Machine (Un)Learning
7 February 2022
Ji Gao
Sanjam Garg
Mohammad Mahmoody
Prashant Nalini Vasudevan
MIACV
AAML
Re-assign community
ArXiv
PDF
HTML
Papers citing
"Deletion Inference, Reconstruction, and Compliance in Machine (Un)Learning"
19 / 19 papers shown
Title
PRUNE: A Patching Based Repair Framework for Certiffable Unlearning of Neural Networks
X. Li
Jingyi Wang
Xiaohan Yuan
Peixin Zhang
Z. Qin
Zhibo Wang
Kui Ren
AAML
MU
42
0
0
10 May 2025
A Framework for Cryptographic Verifiability of End-to-End AI Pipelines
Kar Balan
Robert Learney
Tim Wood
34
0
0
28 Mar 2025
CRFU: Compressive Representation Forgetting Against Privacy Leakage on Machine Unlearning
Weiqi Wang
Chenhan Zhang
Zhiyi Tian
Shushu Liu
Shui Yu
MU
42
0
0
27 Feb 2025
A Review on Machine Unlearning
Haibo Zhang
Toru Nakamura
Takamasa Isohara
Kouichi Sakurai
AILaw
PILM
MU
85
46
0
18 Nov 2024
Game-Theoretic Machine Unlearning: Mitigating Extra Privacy Leakage
Hengzhu Liu
Tianqing Zhu
Lefeng Zhang
Ping Xiong
MU
32
0
0
06 Nov 2024
Position: LLM Unlearning Benchmarks are Weak Measures of Progress
Pratiksha Thaker
Shengyuan Hu
Neil Kale
Yash Maurya
Zhiwei Steven Wu
Virginia Smith
MU
45
10
0
03 Oct 2024
A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks
Hengzhu Liu
Ping Xiong
Tianqing Zhu
Philip S. Yu
27
6
0
10 Jun 2024
Guaranteeing Data Privacy in Federated Unlearning with Dynamic User Participation
Ziyao Liu
Yu Jiang
Weifeng Jiang
Jiale Guo
Jun Zhao
Kwok-Yan Lam
MU
FedML
42
6
0
03 Jun 2024
Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable
Martín Bertrán
Shuai Tang
Michael Kearns
Jamie Morgenstern
Aaron Roth
Zhiwei Steven Wu
AAML
27
5
0
30 May 2024
Machine Unlearning: A Comprehensive Survey
Weiqi Wang
Zhiyi Tian
Chenhan Zhang
Shui Yu
MU
AILaw
32
13
0
13 May 2024
Learn What You Want to Unlearn: Unlearning Inversion Attacks against Machine Unlearning
Hongsheng Hu
Shuo Wang
Tian Dong
Minhui Xue
AAML
16
17
0
04 Apr 2024
Threats, Attacks, and Defenses in Machine Unlearning: A Survey
Ziyao Liu
Huanyi Ye
Chen Chen
Yongsen Zheng
K. Lam
AAML
MU
29
28
0
20 Mar 2024
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
26
43
0
31 Oct 2023
Tight Bounds for Machine Unlearning via Differential Privacy
Yiyang Huang
C. Canonne
MU
17
9
0
02 Sep 2023
Exploring the Landscape of Machine Unlearning: A Comprehensive Survey and Taxonomy
T. Shaik
Xiaohui Tao
Haoran Xie
Lin Li
Xiaofeng Zhu
Qingyuan Li
MU
30
25
0
10 May 2023
SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning
A. Salem
Giovanni Cherubin
David E. Evans
Boris Köpf
Andrew J. Paverd
Anshuman Suri
Shruti Tople
Santiago Zanella Béguelin
31
35
0
21 Dec 2022
Proof of Unlearning: Definitions and Instantiation
Jiasi Weng
Shenglong Yao
Yuefeng Du
Junjie Huang
Jian Weng
Cong Wang
MU
19
12
0
20 Oct 2022
Verifiable and Provably Secure Machine Unlearning
Thorsten Eisenhofer
Doreen Riepel
Varun Chandrasekaran
Esha Ghosh
O. Ohrimenko
Nicolas Papernot
AAML
MU
28
25
0
17 Oct 2022
When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning?
Gavin Brown
Mark Bun
Vitaly Feldman
Adam D. Smith
Kunal Talwar
245
80
0
11 Dec 2020
1