Lifted Variable Elimination with Arbitrary Constraints

  title={Lifted Variable Elimination with Arbitrary Constraints},
  author={Nima Taghipour and Daan Fierens and Jesse Davis and Hendrik Blockeel},
Lifted probabilistic inference algorithms exploit regularities in the structure of graphical models to perform inference more efficiently. More specifically, they identify groups of interchangeable variables and perform inference once for each group, as opposed to once for each variable. The groups are defined by means of constraints, so the flexibility of the grouping is determined by the expressivity of the constraint language. Existing approaches for exact lifted inference rely on (in… CONTINUE READING
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