Private release of graph statistics using ladder functions
- Submitting institution
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The University of Warwick
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 5888
- Type
- E - Conference contribution
- DOI
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10.1145/2723372.2737785
- Title of conference / published proceedings
- ACM SIGMOD 2015
- First page
- 731
- Volume
- -
- Issue
- -
- ISSN
- -
- Open access status
- -
- Month of publication
- May
- Year of publication
- 2015
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
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D - Data Science, Systems and Security
- Citation count
- 27
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Supported by an EC Marie Curie award and published in the top data management conference, this work has been presented as a leading contribution in several surveys and overviews from Harvard (Vadhan, Springer 2017), Tsinghua (Zhu, Li, Zhou, Yu, IEEE TKDE 2017), Boston University (Raskhodnikova, Smith, Encyclopedia of Algorithms, Springer 2016), and University of Illinois-Chicago (Zhu, Li, Zhou, Yu, Springer 2017). It has led to work on publishing social graphs (Chen, Mauw, Ramirez-Cruz, PETS 2020), and connection fingerprints in social networks (Li, Liu, Wang, Liu, Chinese J. Electronics 2018). Our open-source code has been downloaded >100 times from Sourceforge (https://sourceforge.net/projects/ladderfunctions/).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -