Higher-order approximate relational refinement types for mechanism design and differential privacy
- Submitting institution
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University of Dundee
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 39891027
- Type
- E - Conference contribution
- DOI
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10.1145/2676726.2677000
- Title of conference / published proceedings
- Proceedings of the 42nd annual ACM SIGPLAN-SIGACT symposium on principles of programming languages
- First page
- 55
- Volume
- -
- Issue
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- ISSN
- -
- Open access status
- -
- Month of publication
- January
- Year of publication
- 2015
- URL
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- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
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- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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5
- Research group(s)
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-
- Citation count
- 17
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This article contributed to development of what is now one of the predominant approaches for guaranteeing programs as differentially private. It led to further developments from a theoretical perspective (Zhang and Kifer, POPL 2017] and informed practical guidelines for implementing and auditing differentially private systems (Kifer et al., CoRRabs/2002.04049, 2020). It led to NSF Large Collaborative Grant “Computing Over Distributed Sensitive Data” (#1565365), further papers including two by Barthe, Gaboardi et al. at CCS 2016 (16% acceptance rate), and invited talks including at Chalmers University, CEA France, University of Maryland, and Harvard Theory Group.
- Author contribution statement
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- Non-English
- No
- English abstract
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