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        <identifier>oai:drops-oai.dagstuhl.de:23167</identifier>
        <datestamp>2025-10-02T12:41:43Z</datestamp>
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          <dc:title>When Distances Lie: Euclidean Embeddings in the Presence of Outliers and Distance Violations</dc:title>
          <dc:creator>Bentert, Matthias</dc:creator>
          <dc:creator>Fomin, Fedor V.</dc:creator>
          <dc:creator>Golovach, Petr A.</dc:creator>
          <dc:creator>Ramanujan, M. S.</dc:creator>
          <dc:creator>Saurabh, Saket</dc:creator>
          <dc:subject>Parameterized Complexity</dc:subject>
          <dc:subject>Euclidean Embedding</dc:subject>
          <dc:subject>FPT-approximation</dc:subject>
          <dc:description>Distance geometry explores the properties of distance spaces that can be exactly represented as the pairwise Euclidean distances between points in ℝ^d (d ≥ 1), or equivalently, distance spaces that can be isometrically embedded in ℝ^d. In this work, we investigate whether a distance space can be isometrically embedded in ℝ^d after applying a limited number of modifications. Specifically, we focus on two types of modifications: outlier deletion (removing points) and distance modification (adjusting distances between points). The central problem, Euclidean Embedding Editing, asks whether an input distance space on n points can be transformed, using at most k modifications, into a space that is isometrically embeddable in ℝ^d.&#13;
We present several fixed-parameter tractable (FPT) and approximation algorithms for this problem. Our first result is an algorithm that solves Euclidean Embedding Editing in time (dk)^𝒪(d+k) + n^𝒪(1). The core subroutine of this algorithm, which is of independent interest, is a polynomial-time method for compressing the input distance space into an equivalent instance of Euclidean Embedding Editing with 𝒪((dk)²) points.&#13;
For the special but important case of Euclidean Embedding Editing where only outlier deletions are allowed, we improve the parameter dependence of the FPT algorithm and obtain a running time of min{(d+3)^k, 2^{d+k}} ⋅ n^𝒪(1). Additionally, we provide an FPT-approximation algorithm for this problem, which outputs a set of at most 2 ⋅ Opt outliers in time 2^d ⋅ n^{𝒪(1)}. This 2-approximation algorithm improves upon the previous (3+ε)-approximation algorithm by Sidiropoulos, Wang, and Wang [SODA '17]. Furthermore, we complement our algorithms with hardness results motivating our choice of parameterizations.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Matthias Bentert and Fedor V. Fomin and Petr A. Golovach and M. S. Ramanujan and Saket Saurabh</dc:contributor>
          <dc:date>2025</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 332, 41st International Symposium on Computational Geometry (SoCG 2025)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.SoCG.2025.15</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-231672</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2025.15</dc:identifier>
          <dc:language>eng</dc:language>
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