Differential Privacy - An Introduction and an Application

The aim of this talk is to:

  • Give a motivation and introduction to differential privacy;
  • Give a few examples of statistical and machine learning applications that work well with differential privacy;
  • Explain the difficulties of applying differential privacy to queries based on graph structures (like social networks);
  • Introduce my research on making online dating recommendation systems differentially private.

The talk is aimed at a broad audience. However, some math is unavoidable.


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