An Integer Polynomial Programming Based Framework for Lifted MAP Inference

NeurIPS 2014 Somdeb SarkhelDeepak VenugopalParag SinglaVibhav G. Gogate

In this paper, we present a new approach for lifted MAP inference in Markov logic networks (MLNs). The key idea in our approach is to compactly encode the MAP inference problem as an Integer Polynomial Program (IPP) by schematically applying three lifted inference steps to the MLN: lifted decomposition, lifted conditioning, and partial grounding... (read more)

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