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Jaguar: A Primal Algorithm for Conjunctive Query Evaluation in Submodular-Width Time

Summary: Jaguar is a primal, join-adaptive algorithm for conjunctive queries that maintains feasible polymatroids while guiding joins. It achieves O(N^(subw(Q)+ε)) time with a simpler analysis than PANDA and extends to degree-constrained submodular width. (summarized by gpt-5.6-luna on Jul 26 2026)

Paper ID
2034
Venue
PODS
Year
2026
Pagerank
5.093636e-05
Overall Rank
10,159 | 30.31%
DOI
10.1145/3801904

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BibTeX Citation

@inproceedings{khamis_pods26,
        address = {New York, NY, USA},
        series = {{PODS} '26},
        title = {{Jaguar: A Primal Algorithm for Conjunctive Query Evaluation in Submodular-Width Time}},
        url = {https://dl.acm.org/doi/10.1145/3801904},
        doi = {10.1145/3801904},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Khamis, Mahmoud Abo and Chen, Hubie},
        year = {2026}
}

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