Fast Hypertree Decompositions via Linear Programming: Fractional and Generalized
Summary: Ralph computes fractional and generalized hypertree decompositions via LP randomized approximation. MILP/LP heuristics atop Korchemna et al.'s poly-time fractional approximation enable near-optimal decompositions on HyperBench and solving 500 unsolved instances. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Vaishali Surianarayanan (University of California Santa Barbara)
- 2. Anikait Mundhra (University of California Santa Barbara)
- 3. Ajaykrishnan E S (University of California Santa Barbara)
- 4. Daniel Lokshtanov (University of California Santa Barbara)
BibTeX Citation
@inproceedings{surianarayanan_sigmod25,
title = {{Fast Hypertree Decompositions via Linear Programming: Fractional and Generalized}},
author = {Surianarayanan, Vaishali and Mundhra, Anikait and S, Ajaykrishnan E and Lokshtanov, Daniel},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3725296},
url = {https://dl.acm.org/doi/10.1145/3725296},
year = {2025}
}
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