The Value of Collaboration in Convex Machine Learning with Differential Privacy

In this paper, we apply machine learning to distributed private data owned by multiple data owners, entities with access to non-overlapping training datasets. We use noisy, differentially-private gradients to minimize the fitness cost of the machine learning model using stochastic gradient descent....

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Bibliographic Details

Published in:	Proceedings - IEEE Symposium on Security and Privacy pp. 304 - 317
Main Authors:	Wu, Nan, Farokhi, Farhad, Smith, David, Kaafar, Mohamed Ali
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.05.2020
Subjects:	Collaboration Computational modeling Data models Data privacy Differential privacy Machine learning Prediction algorithms Privacy Stochastic gradient algorithm Training
ISSN:	2375-1207
Online Access:	Get full text
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