Trading Off Scalability, Privacy, and Performance in Data Synthesis

Synthetic data has been widely applied in the real world recently. One typical example is the creation of synthetic data for privacy concerned datasets. In this scenario, synthetic data substitute the real data which contains the privacy information, and is used to public testing for machine learnin...

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Veröffentlicht in:	IEEE access 2024, Vol.12, p.26642-26654
Hauptverfasser:	Ling, Xiao, Menzies, Tim, Hazard, Christopher, Shu, Jack, Beel, Jacob
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Biomedical imaging classification Classification algorithms Clustering algorithms Data models Data privacy Engines Generative adversarial networks Homomorphic encryption Machine learning Privacy privacy preservation regression Regression analysis Scalability Synthetic data Synthetic data generation
Online-Zugang:	Volltext
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