Much of the power of probabilistic methods in modelling language comes from their ability to compare several derivations for the same string in the language. An important starting...
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...
Recent advances in non-monotonic semantics of deductive databases provide a simple framework for modeling the even-condition-action rules of active databases. This approach unifie...
Starting from a graphical data model (a subset of the OMT object model), a skeleton of formal specification can be generated and completed to express several constraints and provi...
Conditional random field (CRF) is a popular graphical model for sequence labeling. The flexibility of CRF poses significant computational challenges for training. Using existing o...