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Determination of Plasma Membrane Partitioning for Peripherally-associated Proteins
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Finding the mean in a partition distribution.

Thomas J Glassen1, Timo von Oertzen2,3, Dmitry A Konovalov4

  • 1Department of Psychology, Universität der Bundeswehr München, Werner-Heisenberg-Weg 39, Neubiberg, 85577, Germany.

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|October 14, 2018
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Summary
This summary is machine-generated.

This study introduces an accelerated algorithm for finding the optimal clustering solution from Bayesian Dirichlet Process (DP) mixture models. The new method significantly reduces computation time for identifying the best partition from posterior samples.

Keywords:
Bayesian clusteringDirichlet ProcessMean partitionPartition distance

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Area of Science:

  • Computational Statistics
  • Machine Learning

Background:

  • Bayesian clustering, particularly Dirichlet Processes (DP), yields posterior distributions of partitions.
  • Applied scenarios often require a single, optimal clustering solution from these distributions.
  • Identifying the 'best' partition from a posterior sample is an ongoing research challenge.

Purpose of the Study:

  • To review and enhance an algorithm for approximating the sample mean partition.
  • To improve the computational efficiency of deriving a single clustering solution from DP models.

Main Methods:

  • Utilizes the Hungarian Method to compute distances between partitions for approximating the sample mean.
  • Introduces a faster variant of partition distance reduction.
  • Incorporates an adapted dynamical Hungarian Algorithm for deterministic acceleration.
  • Applies Monte Carlo techniques and dynamic matrix inverse for theoretical speedup.

Main Results:

  • Achieved a runtime complexity up to two orders of magnitude lower than standard methods.
  • A deterministic improvement using a dynamical Hungarian Algorithm yielded at least one order of magnitude decrease.
  • Further theoretical improvements reduced complexity by nearly the square root of an order of magnitude.

Conclusions:

  • The developed mean partition algorithm offers significant acceleration compared to existing methods.
  • The new algorithm is implemented in Java and publicly available on GitHub.