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Fast and Private Max-Sum Diversification

Summary: Introduces differential-private algorithms for max-sum diversification under cardinality and matroid constraints, with near-optimal utility. Surprisingly, the methods can outperform existing non-private algorithms in speed while retaining strong utility under stringent privacy. (summarized by gpt-5.6-luna on Aug 28 2026)

Paper ID
h58739466643c9846
Venue
VLDB
Year
2026
Pagerank
4.9793485e-05
Overall Rank
10,852 | 27.04%
DOI
10.14778/3836663.3836679

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BibTeX Citation

@article{zadicario_vldb26,
        title = {{Fast and Private Max-Sum Diversification}},
        author = {Zadicario, Ron and Milo, Tova},
        journal = {PVLDB},
        series = {{VLDB} '26},
        volume = {19},
        number = {11},
        pages = {3146--3159},
        doi = {10.14778/3836663.3836679},
        url = {https://doi.org/10.14778/3836663.3836679},
        year = {2026}
}

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