26 min listen
Differential Privacy Theory & Practice with Aaron Roth - TWiML Talk #132
FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Differential Privacy Theory & Practice with Aaron Roth - TWiML Talk #132
FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
ratings:
Length:
43 minutes
Released:
Apr 30, 2018
Format:
Podcast episode
Description
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.
Released:
Apr 30, 2018
Format:
Podcast episode
Titles in the series (100)
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