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Individualized PATE: Differentially Private Machine Learning with
  Individual Privacy Guarantees
v1v2v3v4 (latest)

Individualized PATE: Differentially Private Machine Learning with Individual Privacy Guarantees

Proceedings on Privacy Enhancing Technologies (PoPETs), 2022
21 February 2022
Franziska Boenisch
Christopher Muhl
Roy Rinberg
Jannis Ihrig
Adam Dziedzic
ArXiv (abs)PDFHTML

Papers citing "Individualized PATE: Differentially Private Machine Learning with Individual Privacy Guarantees"

12 / 12 papers shown
Title
Gaze3P: Gaze-Based Prediction of User-Perceived Privacy
Gaze3P: Gaze-Based Prediction of User-Perceived Privacy
Mayar Elfares
Pascal Reisert
Ralf Küsters
Andreas Bulling
101
0
0
01 Jul 2025
DP-GPL: Differentially Private Graph Prompt Learning
DP-GPL: Differentially Private Graph Prompt Learning
Jing Xu
Franziska Boenisch
Iyiola Emmanuel Olatunji
Adam Dziedzic
AAML
223
0
0
13 Mar 2025
Controlled privacy leakage propagation throughout overlapping grouped learningIEEE Journal on Selected Areas in Information Theory (JSAIT), 2025
Shahrzad Kiani
Franziska Boenisch
S. Draper
FedML
254
0
0
06 Mar 2025
Guarding the Privacy of Label-Only Access to Neural Network Classifiers via iDP Verification
Guarding the Privacy of Label-Only Access to Neural Network Classifiers via iDP Verification
Anan Kabaha
Dana Drachsler-Cohen
AAML
313
1
0
23 Feb 2025
Privacy Amplification for the Gaussian Mechanism via Bounded Support
Privacy Amplification for the Gaussian Mechanism via Bounded Support
Shengyuan Hu
Saeed Mahloujifar
Virginia Smith
Kamalika Chaudhuri
Chuan Guo
FedML
173
1
0
07 Mar 2024
LLM-based Privacy Data Augmentation Guided by Knowledge Distillation
  with a Distribution Tutor for Medical Text Classification
LLM-based Privacy Data Augmentation Guided by Knowledge Distillation with a Distribution Tutor for Medical Text Classification
Yiping Song
Juhua Zhang
Zhiliang Tian
Yuxin Yang
Shiyu Huang
Dongsheng Li
145
13
0
26 Feb 2024
Personalized Differential Privacy for Ridge Regression
Personalized Differential Privacy for Ridge Regression
Krishna Acharya
Franziska Boenisch
Rakshit Naidu
Juba Ziani
128
5
0
30 Jan 2024
Cross-silo Federated Learning with Record-level Personalized
  Differential Privacy
Cross-silo Federated Learning with Record-level Personalized Differential Privacy
Junxu Liu
Jian Lou
Li Xiong
Jinfei Liu
Xiaofeng Meng
383
23
0
29 Jan 2024
Personalized DP-SGD using Sampling Mechanisms
Personalized DP-SGD using Sampling Mechanisms
Geon Heo
Junseok Seo
Steven Euijong Whang
165
3
0
24 May 2023
Have it your way: Individualized Privacy Assignment for DP-SGD
Have it your way: Individualized Privacy Assignment for DP-SGDNeural Information Processing Systems (NeurIPS), 2023
Franziska Boenisch
Christopher Muhl
Adam Dziedzic
Roy Rinberg
Nicolas Papernot
255
24
0
29 Mar 2023
Cohere: Managing Differential Privacy in Large Scale Systems
Cohere: Managing Differential Privacy in Large Scale SystemsIEEE Symposium on Security and Privacy (IEEE S&P), 2023
Nicolas Küchler
Emanuel Opel
Hidde Lycklama
Alexander Viand
Anwar Hithnawi
161
6
0
20 Jan 2023
Trusted AI in Multi-agent Systems: An Overview of Privacy and Security
  for Distributed Learning
Trusted AI in Multi-agent Systems: An Overview of Privacy and Security for Distributed LearningProceedings of the IEEE (Proc. IEEE), 2022
Chuan Ma
Jun Li
Kang Wei
Bo Liu
Ming Ding
Long Yuan
Zhu Han
H. Vincent Poor
293
63
0
18 Feb 2022
1