Private Machine Learning via Randomised Response

David Barber

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arXiv · 2001.04942

Private Machine Learning via Randomised Response

David Barber

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Abstract

We introduce a general learning framework for private machine learning based on randomised response. Our assumption is that all actors are potentially adversarial and as such we trust only to release a single noisy version of an individual's datapoint. We discuss a general approach that forms a consistent way to estimate the true underlying machine learning model and demonstrate this in the case of logistic regression.

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David Barber. 2020-01-14. Private Machine Learning via Randomised Response. https://arxiv.org/abs/2001.04942

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