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Formalizing Data Deletion in the Context of the Right to be Forgotten

Formalizing Data Deletion in the Context of the Right to be Forgotten

25 February 2020
Sanjam Garg
S. Goldwasser
Prashant Nalini Vasudevan
    AILaw
    MU
ArXivPDFHTML

Papers citing "Formalizing Data Deletion in the Context of the Right to be Forgotten"

20 / 20 papers shown
Title
CRFU: Compressive Representation Forgetting Against Privacy Leakage on Machine Unlearning
Weiqi Wang
Chenhan Zhang
Zhiyi Tian
Shushu Liu
Shui Yu
MU
47
0
0
27 Feb 2025
Position: LLM Unlearning Benchmarks are Weak Measures of Progress
Position: LLM Unlearning Benchmarks are Weak Measures of Progress
Pratiksha Thaker
Shengyuan Hu
Neil Kale
Yash Maurya
Zhiwei Steven Wu
Virginia Smith
MU
53
10
0
03 Oct 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
Knowledge Sanitization of Large Language Models
Knowledge Sanitization of Large Language Models
Yoichi Ishibashi
Hidetoshi Shimodaira
KELM
39
19
0
21 Sep 2023
Training Data Extraction From Pre-trained Language Models: A Survey
Training Data Extraction From Pre-trained Language Models: A Survey
Shotaro Ishihara
32
46
0
25 May 2023
Verifiable and Provably Secure Machine Unlearning
Verifiable and Provably Secure Machine Unlearning
Thorsten Eisenhofer
Doreen Riepel
Varun Chandrasekaran
Esha Ghosh
O. Ohrimenko
Nicolas Papernot
AAML
MU
41
26
0
17 Oct 2022
Algorithms that Approximate Data Removal: New Results and Limitations
Algorithms that Approximate Data Removal: New Results and Limitations
Vinith Suriyakumar
Ashia Wilson
MU
44
27
0
25 Sep 2022
Cryptography with Certified Deletion
Cryptography with Certified Deletion
James Bartusek
Dakshita Khurana
16
26
0
05 Jul 2022
Debugging using Orthogonal Gradient Descent
Debugging using Orthogonal Gradient Descent
Narsimha Chilkuri
C. Eliasmith
26
1
0
17 Jun 2022
Knowledge Removal in Sampling-based Bayesian Inference
Knowledge Removal in Sampling-based Bayesian Inference
Shaopeng Fu
Fengxiang He
Dacheng Tao
BDL
MU
22
27
0
24 Mar 2022
Quantum Proofs of Deletion for Learning with Errors
Quantum Proofs of Deletion for Learning with Errors
Alexander Poremba
19
21
0
03 Mar 2022
Deletion Inference, Reconstruction, and Compliance in Machine
  (Un)Learning
Deletion Inference, Reconstruction, and Compliance in Machine (Un)Learning
Ji Gao
Sanjam Garg
Mohammad Mahmoody
Prashant Nalini Vasudevan
MIACV
AAML
19
22
0
07 Feb 2022
Fast Yet Effective Machine Unlearning
Fast Yet Effective Machine Unlearning
Ayush K Tarun
Vikram S Chundawat
Murari Mandal
Mohan S. Kankanhalli
MU
31
171
0
17 Nov 2021
Survey: Leakage and Privacy at Inference Time
Survey: Leakage and Privacy at Inference Time
Marija Jegorova
Chaitanya Kaul
Charlie Mayor
Alison Q. OÑeil
Alexander Weir
Roderick Murray-Smith
Sotirios A. Tsaftaris
PILM
MIACV
23
71
0
04 Jul 2021
Remember What You Want to Forget: Algorithms for Machine Unlearning
Remember What You Want to Forget: Algorithms for Machine Unlearning
Ayush Sekhari
Jayadev Acharya
Gautam Kamath
A. Suresh
FedML
MU
39
284
0
04 Mar 2021
Coded Machine Unlearning
Coded Machine Unlearning
Nasser Aldaghri
Hessam Mahdavifar
Ahmad Beirami
MIACV
27
37
0
31 Dec 2020
Mixed-Privacy Forgetting in Deep Networks
Mixed-Privacy Forgetting in Deep Networks
Aditya Golatkar
Alessandro Achille
Avinash Ravichandran
M. Polito
Stefano Soatto
CLL
MU
130
160
0
24 Dec 2020
Machine Unlearning for Random Forests
Machine Unlearning for Random Forests
Jonathan Brophy
Daniel Lowd
MU
19
158
0
11 Sep 2020
Towards Probabilistic Verification of Machine Unlearning
Towards Probabilistic Verification of Machine Unlearning
David M. Sommer
Liwei Song
Sameer Wagh
Prateek Mittal
AAML
13
71
0
09 Mar 2020
Machine Unlearning: Linear Filtration for Logit-based Classifiers
Machine Unlearning: Linear Filtration for Logit-based Classifiers
Thomas Baumhauer
Pascal Schöttle
Matthias Zeppelzauer
MU
111
130
0
07 Feb 2020
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