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arXiv · 2502.01120

Lipschitz Decompositions of Finite $\ell_{p}$ Metrics

Robert Krauthgamer·Nir Petruschka
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Abstract

Lipschitz decomposition is a useful tool in the design of efficient algorithms involving metric spaces. While many bounds are known for different families of finite metrics, the optimal parameters for $n$-point subsets of $\ell_p$, for $p > 2$, remained open, see e.g. [Naor, SODA 2017]. We make significant progress on this question and establish the bound $\beta=O(\log^{1-1/p} n)$. Building on prior work, we demonstrate applications of this result to two problems, high-dimensional geometric spanners and distance labeling schemes. In addition, we sharpen a related decomposition bound for $1<p<2$, due to Filtser and Neiman [Algorithmica 2022].

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BibTeXRIS

Robert Krauthgamer, Nir Petruschka. 2025-02-03. Lipschitz Decompositions of Finite $\ell_{p}$ Metrics. https://doi.org/10.4230/lipics.socg.2025.66

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