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Stochastic Submodular Data Forgetting

Summary: Subset-selection data forgetting: given relational D, query log Q and budget B, pick D* (|D*|≤B) to preserve approximate expected query answers. IndepDF and DepDF avoid function evaluations to get submodular-style guarantees with amnesia-like runtime, matching submodular accuracy while scaling. (summarized by gpt-5-mini on Feb 11 2026)

Paper ID
he7442ae75157c171
Venue
SIGMOD
Year
2026
Pagerank
4.9605343e-05
Overall Rank
10,669 | 28.49%
DOI
10.1145/3769830
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BibTeX Citation

@inproceedings{rico_sigmod26,
        title = {{Stochastic Submodular Data Forgetting}},
        author = {Rico, Ramon and Siebes, Arno and Velegrakis, Yannis},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3769830},
        url = {https://dl.acm.org/doi/10.1145/3769830},
        year = {2026}
}

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