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        <datestamp>2024-03-06T10:35:20Z</datestamp>
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          <dc:title>Communication Complexity of Set-Disjointness for All Probabilities</dc:title>
          <dc:creator>Göös, Mika</dc:creator>
          <dc:creator>Watson, Thomas</dc:creator>
          <dc:subject>Communication Complexity</dc:subject>
          <dc:subject>Set-Disjointness</dc:subject>
          <dc:subject>All Probabilities</dc:subject>
          <dc:description>We study set-disjointness in a generalized model of randomized two-party communication where the probability of acceptance must be at least alpha(n) on yes-inputs and at most beta(n) on no-inputs, for some functions alpha(n)&gt;beta(n). Our main result is a complete characterization of the private-coin communication complexity of set-disjointness for all functions alpha and beta, and a near-complete characterization for public-coin protocols. In particular, we obtain a simple proof of a theorem of Braverman and Moitra (STOC 2013), who studied the case where alpha=1/2+epsilon(n) and beta=1/2-epsilon(n). The following contributions play a crucial role in our characterization and are interesting in their own right.&#13;
&#13;
(1) We introduce two communication analogues of the classical complexity class that captures small bounded-error computations: we define a "restricted" class SBP (which lies between MA and AM) and an "unrestricted" class USBP. The distinction between them is analogous to the distinction between the well-known communication classes PP and UPP.&#13;
&#13;
(2) We show that the SBP communication complexity is precisely captured by the classical corruption lower bound method. This sharpens a theorem of Klauck (CCC 2003).&#13;
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(3) We use information complexity arguments to prove a linear lower bound on the USBP complexity of set-disjointness.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Mika Göös and Thomas Watson</dc:contributor>
          <dc:date>2014</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 28, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2014)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.APPROX-RANDOM.2014.721</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-47342</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX-RANDOM.2014.721</dc:identifier>
          <dc:language>eng</dc:language>
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