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An innovative programming framework for authoring accurate, efficient and private algorithms
Designing a programming framework for writing complex yet safe differential privacy programs is no small task. This paper co-authored by Tumult Labs founders laid the foundation of the privacy framework used by our customers.
Summary:
While differential privacy has emerged as the leading solution for achieving statistically sound, private summaries, designing custom private, efficient, and accurate algorithms is still very complex. We describe a novel programming framework and system, EKTELO, for implementing both existing and new privacy algorithms. The novelty in our framework lies in its ability to support accurate, efficient and private programs. In this article we describe the design and architecture of the EKTELO system, followed by demonstrations of how expressive and safe it is to use.
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