<?xml version="1.0" encoding="UTF-8"?>
<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd">
  <responseDate>2026-07-23T19:19:43Z</responseDate>
  <request identifier="17148" metadataPrefix="oai_dc" verb="GetRecord">https://drops.dagstuhl.de/oai</request>
  <GetRecord>
    <record>
      <header>
        <identifier>oai:drops-oai.dagstuhl.de:17148</identifier>
        <datestamp>2024-03-06T10:59:05Z</datestamp>
        <setSpec>ddc:004</setSpec>
        <setSpec>open_access</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>Lifting with Inner Functions of Polynomial Discrepancy</dc:title>
          <dc:creator>Manor, Yahel</dc:creator>
          <dc:creator>Meir, Or</dc:creator>
          <dc:subject>Lifting</dc:subject>
          <dc:subject>communication complexity</dc:subject>
          <dc:subject>query complexity</dc:subject>
          <dc:subject>discrepancy</dc:subject>
          <dc:description>Lifting theorems are theorems that bound the communication complexity of a composed function f∘gⁿ in terms of the query complexity of f and the communication complexity of g. Such theorems constitute a powerful generalization of direct-sum theorems for g, and have seen numerous applications in recent years.&#13;
We prove a new lifting theorem that works for every two functions f,g such that the discrepancy of g is at most inverse polynomial in the input length of f. Our result is a significant generalization of the known direct-sum theorem for discrepancy, and extends the range of inner functions g for which lifting theorems hold.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Yahel Manor and Or Meir</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>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
          <dc:type>publishedVersion</dc:type>
          <dc:format>application/pdf</dc:format>
          <dc:identifier>doi:10.4230/LIPIcs.APPROX/RANDOM.2022.26</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-171486</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2022.26</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
        </oai_dc:dc>
      </metadata>
    </record>
  </GetRecord>
</OAI-PMH>
