Membership Inference Attack: Primer & Case Study

Machine learning models depend on large troves of data to develop and improve their inference / prediction capabilities. These models generalize their abilities, but inevitably some of their training data is encoded or memorized within their trained parameters. This post explores a method of quantifying model memorization, factors that make models more prone to memorization, and provides some mitigations against memorization. ...

July 1, 2023 · 25 min · D.Moreno

Differential Privacy: Primer & Laplace Case Study

This post serves as a primer to Differential Privacy: presenting an intuitive foundation for the definition, proceeding to some math, and finally presenting a case study to demonstrate some key concepts. ...

November 10, 2022 · 13 min · D.Moreno