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Quantum DNF Learnability Revisited

  • Jeffrey C. Jackson
  • Christino Tamon
  • Tomoyuki Yamakami
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2387)

Abstract

We describe a quantum PAC learning algorithm for DNF formulae under the uniform distribution with a query complexity of ~O(s3/ + s 2/ 2), where s is the size of DNF formula and is the PAC error accuracy. If s and 1/∈ are comparable, this gives a modest improvement over a previously known classical query complexity of Õ(ns 2 /te 2). We also show a lower bound of Ω(slogn/n on the query complexity of any quantum PAC algorithm for learning a DNF of size s with n inputs under the uniform distribution.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Jeffrey C. Jackson
    • 1
  • Christino Tamon
    • 2
  • Tomoyuki Yamakami
    • 3
  1. 1.Duquesne UniversityPittsburghUSA
  2. 2.Clarkson UniversityPotsdamUSA
  3. 3.University of OttawaOttawaCanada

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