Private Machine Learning via Randomised Response — mentioned by razcle

Thu, 04 Feb 2021 20:58:23 GMT

TL;DR I think its complementary. Synthetic data is particularly valuable when even the unlabelled data is expensive to obtain. For example if you want to train a driverless car, you may never see an ambulance driving at night in the rain even if you drive for thousands of miles. In that case, being able to synthesise data makes a lot of sense and we have lots of tools for computer graphics that make this easy. Synthetic data can also be useful to share data when there are privacy concerns but my own feeling here is that there are better approaches to privacy preservation, like federated…

Paper and discussion history. A mention is not an endorsement.

Private Machine Learning via Randomised Response · HackerPapers discussions

Private Machine Learning via Randomised Response — mentioned by razcle