Revealing Network Structure, Confidentially: Improved Rates for Node-Private Graphon Estimation

2018 IEEE 59TH ANNUAL SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE (FOCS), pp. 533.0-543, 2018.

Cited by: 0|Bibtex|Views74|DOI:https://doi.org/10.1109/FOCS.2018.00057
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

Motivated by growing concerns over ensuring privacy on social networks, we develop new algorithms and impossibility results for fitting complex statistical models to network data subject to rigorous privacy guarantees. We consider the so-called node-differentially private algorithms, which compute information about a graph or network whil...More

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