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Differential Privacy in the Wild: A tutorial on current practices & open challenges

Summary: Tutorial on differential privacy: foundations and state-of-the-art private algorithms for tabular data, plus real-world applications. Explores practical adoption barriers in industry/government and open challenges for applying DP to complex data and deployments. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11484
Venue
VLDB
Year
2016
Pagerank
5.8973335e-05
Overall Rank
6,370 | 56.30%
DOI
10.14778/3007263.3007322

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{machanavajjhala_vldb16,
        title = {{Differential Privacy in the Wild: A tutorial on current practices \& open challenges}},
        author = {Machanavajjhala, Ashwin and He, Xi and Hay, Michael},
        journal = {PVLDB},
        series = {{VLDB} '16},
        volume = {9},
        number = {13},
        doi = {10.14778/3007263.3007322},
        url = {https://doi.org/10.14778/3007263.3007322},
        year = {2016}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
1,837 Marginal Release Under Local Differential Privacy 2018 SIGMOD 9.6443703e-05
5,613 Differential Privacy in the Wild: A Tutorial on Current Practices & Open Challenges 2017 SIGMOD 6.1501263e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 16 of 16 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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