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Sequence data plays an important role in data analysis applications, such as sequence classification. One important aspect of sequence data analysis is to obtain the labeled sequence data and use a machine learning model to predict the sequence structures. Conditional Random Fields (CRF) is such a machine learning method which is popular used in sequential data analysis. This is because that CRF can...
Chain graph (CG) is a hybrid probabilistic graphical model (PGM) capable of modeling heterogeneous relationships among random variables. So far, however, its application in image and video analysis is very limited due to lack of principled learning and inference methods for a CG of general topology. To overcome this limitation, we introduce methods to extend the conventional chain-like CG model to...
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