1. Polynomial Time Samplable Distributions
- Author
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Tomoyuki Yamakami
- Subjects
Average-case complexity ,Statistics and Probability ,average-case complexity ,Control and Optimization ,General Mathematics ,Computer Science::Computational Complexity ,Matrix polynomial ,Square-free polynomial ,Combinatorics ,symbols.namesake ,Structural complexity theory ,TheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITY ,ComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION ,Degree of a polynomial ,domination condition ,Time complexity ,Mathematics ,Discrete mathematics ,strong one-way functions ,Numerical Analysis ,Algebra and Number Theory ,Alternating polynomial ,Applied Mathematics ,symbols ,sampling algorithm ,Gibbs sampling - Abstract
This paper studies the complexity of the polynomial-time samplable ( P -samplable) distributions, which can be approximated within an exponentially small factor by sampling algorithms in time polynomial in the length of their outputs. The paper shows that common assumptions in complexity theory yield the separation of polynomial-time samplable distributions from the polynomial-time computable distributions with respect to polynomial domination, average-polynomial domination, polynomial equivalence, and average-polynomial equivalence.
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