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        <identifier>oai:drops-oai.dagstuhl.de:11253</identifier>
        <datestamp>2024-03-06T10:47:48Z</datestamp>
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          <dc:title>Lifted Multiplicity Codes and the Disjoint Repair Group Property</dc:title>
          <dc:creator>Li, Ray</dc:creator>
          <dc:creator>Wootters, Mary</dc:creator>
          <dc:subject>Lifted codes</dc:subject>
          <dc:subject>Multiplicity codes</dc:subject>
          <dc:subject>Disjoint repair group property</dc:subject>
          <dc:subject>PIR code</dc:subject>
          <dc:subject>Coding theory</dc:subject>
          <dc:description>Lifted Reed Solomon Codes (Guo, Kopparty, Sudan 2013) were introduced in the context of locally correctable and testable codes. They are multivariate polynomials whose restriction to any line is a codeword of a Reed-Solomon code. We consider a generalization of their construction, which we call lifted multiplicity codes. These are multivariate polynomial codes whose restriction to any line is a codeword of a multiplicity code (Kopparty, Saraf, Yekhanin 2014). We show that lifted multiplicity codes have a better trade-off between redundancy and a notion of locality called the t-disjoint-repair-group property than previously known constructions. More precisely, we show that, for t &lt;=sqrt{N}, lifted multiplicity codes with length N and redundancy O(t^{0.585} sqrt{N}) have the property that any symbol of a codeword can be reconstructed in t different ways, each using a disjoint subset of the other coordinates. This gives the best known trade-off for this problem for any super-constant t &lt; sqrt{N}. We also give an alternative analysis of lifted Reed Solomon codes using dual codes, which may be of independent interest.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Ray Li and Mary Wootters</dc:contributor>
          <dc:date>2019</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 145, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2019)</dc:relation>
          <dc:type>InProceedings</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.APPROX-RANDOM.2019.38</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-112539</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX-RANDOM.2019.38</dc:identifier>
          <dc:language>eng</dc:language>
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