An Assessment of the Application of Private Aggregation of Ensemble Models to Sensible Data

An Assessment of the Application of Private Aggregation of Ensemble Models to Sensible Data

This paper explores the use of Private Aggregation of Teacher Ensembles (PATE) in a setting where students have their own private data that cannot be revealed as is to the ensemble. We propose a privacy model that introduces a local differentially private mechanism to protect student data. We implem...

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Bibliographic Details
Main Authors: Sergio Yovine, Franz Mayr, Sebastián Sosa, Ramiro Visca
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Machine Learning and Knowledge Extraction
Subjects:
machine learning
differential privacy
private aggregation of teacher ensemble
Online Access:https://www.mdpi.com/2504-4990/3/4/39

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