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Minimum Coresets for Maxima Representation of Multidimensional Data

Summary: Introduce the minimum ε-coreset problem for maxima representation (preserving max inner products in any direction) and give an optimal polynomial-time algorithm in 2D via a reduction to the shortest directed cycle. Prove NP-hardness for d≥3, provide poly-time approximation algorithms for fixed d, and validate empirically on real and synthetic data. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1849
Venue
PODS
Year
2021
Pagerank
5.1997534e-05
Overall Rank
9,899 | 32.09%
DOI
10.1145/3452021.3458322

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{wang_pods21,
        address = {New York, NY, USA},
        series = {{PODS} '21},
        title = {{Minimum Coresets for Maxima Representation of Multidimensional Data}},
        url = {https://dl.acm.org/doi/10.1145/3452021.3458322},
        doi = {10.1145/3452021.3458322},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Wang, Yanhao and Mathioudakis, Michael and Li, Yuchen and Tan, Kian-Lee},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
9,393 Happiness Maximizing Sets under Group Fairness Constraints 2023 VLDB 5.2755515e-05
11,397 rkHit: Representative Query with Uncertain Preference 2023 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

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