Differentially private Bayesian learning on distributed data

news
21/12/2017
A group of researchers at the University of Helsinki has published a paper at the machine learning conference NIPS on a new method to keep private data collected and processed by AI technologies. Using the concept of differential privacy, the method seeks to guarantee that the published model or result can reveal only limited information on each data subject.