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        <identifier>oai:drops-oai.dagstuhl.de:17217</identifier>
        <datestamp>2024-03-06T10:59:15Z</datestamp>
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          <dc:title>Fast Distributed Vertex Splitting with Applications</dc:title>
          <dc:creator>Halldórsson, Magnús M.</dc:creator>
          <dc:creator>Maus, Yannic</dc:creator>
          <dc:creator>Nolin, Alexandre</dc:creator>
          <dc:subject>Graph problems</dc:subject>
          <dc:subject>Edge coloring</dc:subject>
          <dc:subject>List coloring</dc:subject>
          <dc:subject>Lovász local lemma</dc:subject>
          <dc:subject>LOCAL model</dc:subject>
          <dc:subject>CONGEST model</dc:subject>
          <dc:subject>Distributed computing</dc:subject>
          <dc:description>We present poly log log n-round randomized distributed algorithms to compute vertex splittings, a partition of the vertices of a graph into k parts such that a node of degree d(u) has ≈ d(u)/k neighbors in each part. Our techniques can be seen as the first progress towards general poly log log n-round algorithms for the Lovász Local Lemma. &#13;
As the main application of our result, we obtain a randomized poly log log n-round CONGEST algorithm for (1+ε)Δ-edge coloring n-node graphs of sufficiently large constant maximum degree Δ, for any ε &gt; 0. Further, our results improve the computation of defective colorings and certain tight list coloring problems. All the results improve the state-of-the-art round complexity exponentially, even in the LOCAL model.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Magnús M. Halldórsson and Yannic Maus and Alexandre Nolin</dc:contributor>
          <dc:date>2022</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 246, 36th International Symposium on Distributed Computing (DISC 2022)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.DISC.2022.26</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-172176</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2022.26</dc:identifier>
          <dc:language>eng</dc:language>
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