Estimation and Marginalization Using the Kikuchi Approximation Methods

@article{Pakzad2005EstimationAM,
  title={Estimation and Marginalization Using the Kikuchi Approximation Methods},
  author={Payam Pakzad and Venkat Anantharam},
  journal={Neural Computation},
  year={2005},
  volume={17},
  pages={1836-1873}
}
In this letter, we examine a general method of approximation, known as the Kikuchi approximation method, for finding the marginals of a product distribution, as well as the corresponding partition function. The Kikuchi approximation method defines a certain constrained optimization problem, called the Kikuchi problem, and treats its stationary points as approximations to the desired marginals. We show how to associate a graph to any Kikuchi problem and describe a class of local message-passing… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 30 references

Low complexity, high performance algorithms for estimation and decoding

  • P. Pakzad
  • Unpublished doctoral dissertation, University of…
  • 2004
Highly Influential
8 Excerpts

Error control systems for digital communication and storage

  • S. Wicker
  • Upper Saddle River, NJ: Prentice Hall.
  • 1995
Highly Influential
5 Excerpts

Enumerative combinatorics (Vol

  • R. Stanley
  • 1). Monterey, CA: Wadsworth & Brooks/Cole.
  • 1986
Highly Influential
3 Excerpts

A theory of cooperative phenomena

  • R. Kikuchi
  • Phys . Rev .
  • 1951
Highly Influential
3 Excerpts

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