English

Chaining, Group Leverage Score Overestimates, and Fast Spectral Hypergraph Sparsification

Data Structures and Algorithms 2022-09-22 v1 Probability

Abstract

We present an algorithm that given any nn-vertex, mm-edge, rank rr hypergraph constructs a spectral sparsifier with O(nε2lognlogr)O(n \varepsilon^{-2} \log n \log r) hyperedges in nearly-linear O~(mr)\widetilde{O}(mr) time. This improves in both size and efficiency over a line of work (Bansal-Svensson-Trevisan 2019, Kapralov-Krauthgamer-Tardos-Yoshida 2021) for which the previous best size was O(min{nε4log3n,nr3ε2logn})O(\min\{n \varepsilon^{-4} \log^3 n,nr^3 \varepsilon^{-2} \log n\}) and runtime was O~(mr+nO(1))\widetilde{O}(mr + n^{O(1)}). Independent Result: In an independent work, Lee (Lee 2022) also shows how to compute a spectral hypergraph sparsifier with O(nε2lognlogr)O(n \varepsilon^{-2} \log n \log r) hyperedges.

Keywords

Cite

@article{arxiv.2209.10539,
  title  = {Chaining, Group Leverage Score Overestimates, and Fast Spectral Hypergraph Sparsification},
  author = {Arun Jambulapati and Yang P. Liu and Aaron Sidford},
  journal= {arXiv preprint arXiv:2209.10539},
  year   = {2022}
}
R2 v1 2026-06-28T01:50:29.439Z