Privacy Auditing in Differential Private Machine Learning: The Current Trends
Differential privacy has recently gained prominence, especially in the context of private machine learning. While the definition of differential privacy makes it possible to provably limit the amount of information leaked by an algorithm, practical implementations of differentially private algorithm...
Saved in:
Main Authors: | Ivars Namatevs, Kaspars Sudars, Arturs Nikulins, Kaspars Ozols |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/15/2/647 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Study on choosing the parameter ε in differential privacy
by: Xian-mang HE, et al.
Published: (2015-12-01) -
Privacy view and target of differential privacy
by: Jingyu JIA, et al.
Published: (2023-10-01) -
Privacy level evaluation of differential privacy for time series based on filtering theory
by: Wen-jun XIONG, et al.
Published: (2017-05-01) -
Trajectory differential privacy protection mechanism based on prediction and sliding window
by: Ayong YE, et al.
Published: (2020-04-01) -
Differentially private sequence generative adversarial networks for data privacy masking
by: Yu ZHANG, et al.
Published: (2020-08-01)