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        <identifier>oai:drops-oai.dagstuhl.de:17521</identifier>
        <datestamp>2024-03-06T10:59:48Z</datestamp>
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          <dc:title>Certification with an NP Oracle</dc:title>
          <dc:creator>Blanc, Guy</dc:creator>
          <dc:creator>Koch, Caleb</dc:creator>
          <dc:creator>Lange, Jane</dc:creator>
          <dc:creator>Strassle, Carmen</dc:creator>
          <dc:creator>Tan, Li-Yang</dc:creator>
          <dc:subject>Certificate complexity</dc:subject>
          <dc:subject>Boolean functions</dc:subject>
          <dc:subject>polynomial hierarchy</dc:subject>
          <dc:subject>hardness of approximation</dc:subject>
          <dc:description>In the certification problem, the algorithm is given a function f with certificate complexity k and an input x^⋆, and the goal is to find a certificate of size ≤ poly(k) for f’s value at x^⋆. This problem is in NP^NP, and assuming 𝖯 ≠ NP, is not in 𝖯. Prior works, dating back to Valiant in 1984, have therefore sought to design efficient algorithms by imposing assumptions on f such as monotonicity. &#13;
Our first result is a BPP^NP algorithm for the general problem. The key ingredient is a new notion of the balanced influence of variables, a natural variant of influence that corrects for the bias of the function. Balanced influences can be accurately estimated via uniform generation, and classic BPP^NP algorithms are known for the latter task. &#13;
We then consider certification with stricter instance-wise guarantees: for each x^⋆, find a certificate whose size scales with that of the smallest certificate for x^⋆. In sharp contrast with our first result, we show that this problem is NP^NP-hard even to approximate. We obtain an optimal inapproximability ratio, adding to a small handful of problems in the higher levels of the polynomial hierarchy for which optimal inapproximability is known. Our proof involves the novel use of bit-fixing dispersers for gap amplification.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Guy Blanc and Caleb Koch and Jane Lange and Carmen Strassle and Li-Yang Tan</dc:contributor>
          <dc:date>2023</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 251, 14th Innovations in Theoretical Computer Science Conference (ITCS 2023)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.ITCS.2023.18</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-175217</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2023.18</dc:identifier>
          <dc:language>eng</dc:language>
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