Partition-based Anytime Approximation for Belief

  title={Partition-based Anytime Approximation for Belief},
  author={UpdatingRobert Mateescu},
  • UpdatingRobert Mateescu
  • Published 2001
The paper presents a parameterized approximation scheme for probabilistic inference. The scheme, called Mini-Clustering (MC) extends the partition-based approximation offered by mini-bucket elimination, to tree de-compositions. The beneet of this extension is that all single variable beliefs are computed (approximately) at once, using a two-phase message-passing process along the cluster tree. The resulting approximation scheme is governed by a controlling parameter, "z" that allows adjustable… CONTINUE READING


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