Differential Privacy Theory & Practice with Aaron Roth - TWiML Talk #132 episode artwork

EPISODE · Apr 30, 2018 · 42 MIN

Differential Privacy Theory & Practice with Aaron Roth - TWiML Talk #132

from The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) · host Sam Charrington

In the first episode of our Differential Privacy series, I'm joined by Aaron Roth, associate professor of computer science and information science at the University of Pennsylvania. Aaron is first and foremost a theoretician, and our conversation starts with him helping us understand the context and theory behind differential privacy, a research area he was fortunate to begin pursuing at its inception. We explore the application of differential privacy to machine learning systems, including the costs and challenges of doing so. Aaron discusses as well quite a few examples of differential privacy in action, including work being done at Google, Apple and the US Census Bureau, along with some of the major research directions currently being explored in the field. The notes for this show can be found at twimlai.com/talk/132.

Episode metadata supplied by the publisher feed · Published Apr 30, 2018

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Differential Privacy Theory & Practice with Aaron Roth - TWiML Talk #132

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