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Rankable distributions do not provide harder instances than uniform distributions

  • Jay Belanger
  • Jie Wang
Session 7B: Complexity Theory
Part of the Lecture Notes in Computer Science book series (LNCS, volume 959)

Abstract

We show that polynomially rankable distributions, proposed in [RS93], do not provide harder instances than uniform distributions for NP problems. In particular, we show that if Levin's randomized tiling problem is solvable in polynomial time on average, then every NP problem under any p-rankable distribution is solvable in average polynomial time with respect to rankability. One of the motivations for polynomially rankable distributions was to get average-case hierarchies, and we present a reasonably tight hierarchy result for average-case complexity classes under p-time computable distributions.

Keywords

Turing Machine Ranking Function Deterministic Algorithm Rankable Distribution Hard Instance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Jay Belanger
    • 1
  • Jie Wang
    • 2
  1. 1.Div. of Math & Computer ScienceNortheast Missouri State Univ.Kirksville
  2. 2.Dept. of Mathematical SciencesUniv. of North Carolina at GreensboroGreensboro

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