Practical Differential Privacy at LinkedIn with Ryan Rogers - #346

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

Today we’re joined by Ryan Rogers, Senior Software Engineer at LinkedIn, to discuss his paper “Practical Differentially Private Top-k Selection with Pay-what-you-get Composition.” In our conversation, we discuss how LinkedIn allows its data scientists to access aggregate user data for exploratory analytics while maintaining its users’ privacy through differential privacy, and the connection between a common algorithm for implementing differential privacy, the exponential mechanism, and Gumbel noise.

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This episode is 33 minutes long.

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This episode was published on February 7, 2020.

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