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Abstract: A Hidden Markov Model HMM is a common statistical model which is widelyused for analysis of biological sequence data and other sequential phenomena.In the present paper we show how HMMs can be extended with side-constraints andpresent constraint solving techniques for efficient inference. Defining HMMswith side-constraints in Constraint Logic Programming have advantages in termsof more compact expression and pruning opportunities during inference.We present a PRISM-based framework for extending HMMs with side-constraintsand show how well-known constraints such as cardinality and all different areintegrated. We experimentally validate our approach on the biologicallymotivated problem of global pairwise alignment.



Author: Henning Christiansen, Christian Theil Have, Ole Torp Lassen, Matthieu Petit

Source: https://arxiv.org/







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