SoK: Descriptive Statistics Under Local Differential Privacy -- Raw Results
Raab, René; Berrang, Pascal; Gerhart, Paul; Schröder, Dominique;
SoK: Descriptive Statistics Under Local Differential Privacy -- Raw Results
Raw Results accompanying the code for the paper "SoK: Descriptive Statistics Under Local Differential Privacy" accepted at PETS 2025. The code can be found here: https://github.com/mad-lab-fau/sok-ldp-data-analysis An eprint is available at https://eprint.iacr.org/2024/1464. [Citation will follow as soon as the paper is published]
- University of Erlangen-Nuremberg Germany
- University of Birmingham United Kingdom
- TU Wien Austria
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
citations
Citations provided by BIP!
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
Popularity provided by BIP! 0
Average
Average
Average