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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Veröffentlicht in:	Proceedings - IEEE Symposium on Security and Privacy S. 304 - 317
Hauptverfasser:	Wu, Nan, Farokhi, Farhad, Smith, David, Kaafar, Mohamed Ali
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.05.2020
Schlagworte:	Collaboration Computational modeling Data models Data privacy Differential privacy Machine learning Prediction algorithms Privacy Stochastic gradient algorithm Training
ISSN:	2375-1207
Online-Zugang:	Volltext
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