A Delayed Column Generation Strategy for Exact k-Bounded MAP Inference in Markov Logic Networks

Details A Delayed Column Generation Strategy for Exact k-Bounded MAP Inference in Markov Logic Networks A Delayed Column Generation Strategy for Exact k-Bounded MAP Inference in Markov Logic Networks

2012-03-15

arxiv.org/abs/1203.3499v1

Computer Science

Artificial Intelligence

Appears in Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (UAI2010)

Scientific paper

The paper introduces k-bounded MAP inference, a parameterization of MAP inference in Markov logic networks. k-Bounded MAP states are MAP states with at most k active ground atoms of hidden (non-evidence) predicates. We present a novel delayed column generation algorithm and provide empirical evidence that the algorithm efficiently computes k-bounded MAP states for meaningful real-world graph matching problems. The underlying idea is that, instead of solving one large optimization problem, it is often more efficient to tackle several small ones.

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