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        <identifier>oai:drops-oai.dagstuhl.de:17137</identifier>
        <datestamp>2024-03-06T10:59:03Z</datestamp>
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          <dc:title>Tight Chernoff-Like Bounds Under Limited Independence</dc:title>
          <dc:creator>Skorski, Maciej</dc:creator>
          <dc:subject>concentration inequalities</dc:subject>
          <dc:subject>tail bounds</dc:subject>
          <dc:subject>limited independence</dc:subject>
          <dc:subject>k-wise independence</dc:subject>
          <dc:description>This paper develops sharp bounds on moments of sums of k-wise independent bounded random variables, under constrained average variance. The result closes the problem addressed in part in the previous works of Schmidt et al. and Bellare, Rompel. The work also discusses other applications of independent interests, such as asymptotically sharp bounds on binomial moments.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Maciej Skorski</dc:contributor>
          <dc:date>2022</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 245, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2022)</dc:relation>
          <dc:type>InProceedings</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.APPROX/RANDOM.2022.15</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-171372</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2022.15</dc:identifier>
          <dc:language>eng</dc:language>
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