1 citations · 1 across the 5 of their papers we have counts for
5 papers
Interpreting Network Differential Privacy
Jonathan Hehir, Xiaoyue Niu, Aleksandra Slavkovic
How do we interpret the differential privacy (DP) guarantee for network data? We take a deep dive into a popular form of network DP (--edge DP) to find that many of it…
Easier Estimation of Extremes under Randomized Response
Jonathan Hehir
In this brief note, we consider estimation of the bitwise combination observing a set of noisy bits that represent…
Sketch-Flip-Merge: Mergeable Sketches for Private Distinct Counting
Jonathan Hehir, Daniel Ting, Graham Cormode
Data sketching is a critical tool for distinct counting, enabling multisets to be represented by compact summaries that admit fast cardinality estimates. Because sketches may be me…
Perfect Spectral Clustering with Discrete Covariates
Jonathan Hehir, Xiaoyue Niu, Aleksandra Slavkovic
Among community detection methods, spectral clustering enjoys two desirable properties: computational efficiency and theoretical guarantees of consistency. Most studies of spectral…
Consistent Spectral Clustering of Network Block Models under Local Differential Privacy
Jonathan Hehir, Aleksandra Slavkovic, Xiaoyue Niu
The stochastic block model (SBM) and degree-corrected block model (DCBM) are network models often selected as the fundamental setting in which to analyze the theoretical properties…