Private Machine Learning via Randomised Response
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.
- Publication:
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arXiv e-prints
- Pub Date:
- January 2020
- DOI:
- 10.48550/arXiv.2001.04942
- arXiv:
- arXiv:2001.04942
- Bibcode:
- 2020arXiv200104942B
- Keywords:
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- Computer Science - Machine Learning;
- Statistics - Machine Learning