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Privacy-preserving data sharing via probabilistic modeling
Differential privacy allows quantifying privacy loss resulting from accession of sensitive personal data. Repeated accesses to underlying data incur increasing loss. Releasing data as privacy-preserving synthetic data would avoid this limitation but would leave open the problem of designing what kin...
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| Vydáno v: | Patterns (N Y) |
|---|---|
| Hlavní autoři: | , , , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Elsevier
2021
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8276015/ https://ncbi.nlm.nih.gov/pubmed/34286296 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.patter.2021.100271 |
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