2008 ImprovingtheAccuracyandEfficien

• (Riedel, 2008) ⇒ Sebastian Riedel. (2008). “Improving the Accuracy and Efficiency of MAP Inference for Markov Logic.” In: Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence, UAI 2008.

Subject Headings: MAP Inference.

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• http://scholar.google.com/scholar?q=%222008%22+Improving+the+Accuracy+and+Efficiency+of+MAP+Inference+for+Markov+Logic

Quotes

Abstract

In this work we present Cutting Plane Inference (CPI), a Maximum A Posteriori (MAP) inference method for Statistical Relational Learning. Framed in terms of Markov Logic and inspired by the Cutting Plane Method, it can be seen as a meta algorithm that instantiates small parts of a large and complex Markov Network and then solves these using a conventional MAP method. We evaluate CPI on two tasks, Semantic Role Labelling and Joint Entity Resolution, while plugging in two different MAP inference methods: the current method of choice for MAP inference in Markov Logic, MaxWalkSAT, and Integer Linear Programming. We observe that when used with CPI both methods are significantly faster than when used alone. In addition, CPI improves the accuracy of MaxWalkSAT and maintains the exactness of Integer Linear Programming.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2008 ImprovingtheAccuracyandEfficien	Sebastian Riedel			Improving the Accuracy and Efficiency of MAP Inference for Markov Logic						2008