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The inventors have developed machine learning methods that enable secure training of deep neural networks over multiple data sources. These technologies are useful in fields where data privacy is critical, such as healthcare and finance.

This technology would appeal to companies and institutions who process large quantities of data in order to make estimations or inferences, and especially those who deal with private or otherwise sensitive data. This system allows for the robust data processing required to train neural networks, while protecting the particulars of the data from unauthorized viewing. As such, this technology has direct applications in financial and medical institutions, where data security is critical, but informed estimations and analyses are essential to the operations of the organization