FriendlyCore: A novel differentially private aggregation framework

Posted by Haim Kaplan and Yishay Mansour, Research Scientists, Google Research Differential privacy (DP) machine learning algorithms protect user data by limiting the effect of each data point on an aggregated output with a mathematical guarantee. Intuitively the guarantee implies that changing a single user’s contribution should not significantly change the output distribution of the DP algorithm. However, DP algorithms tend to be less accurate than their non-private counterparts because sati...

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