Consistent Spectral Clustering of Network Block Models under Local Differential Privacy is a research paper published in Journal of Privacy and Confidentiality (2022). On theSindex it has a DataRank of 0.
Scored on demand from live citation data
Linked data & code
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
NIAID NIH HHS
Grant: R01 AI136664
National Science Foundation
Grant: 1853209
Formal Privacy for Complex Data Objects
National Institutes of Health
Grant: 1R01AI136664-01
Statistical Models for Estimating and Projecting HIV/AIDS Epidemics
FWCI
0.00
Citation Percentile
0.0%
Fields of Study
Keywords
Sustainable Development Goals
Consistent Spectral Clustering of Network Block Models under Local Differential Privacy
private-spectral-clustering: Spectral Clustering with Edge-Flip Differential Privacy
private-spectral-clustering: Spectral Clustering with Edge-Flip Differential Privacy