The Value of Collaboration in Convex Machine Learning with Differential Privacy

24 Jun 2019Nan WuFarhad FarokhiDavid SmithMohamed Ali Kaafar

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... (read more)

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