UML semantic variation points provide intentional degrees of freedom for the interpretation of the metamodel semantics. The interest of semantic variation points is that UML now b...
Conditional random fields (CRFs) have been quite successful in various machine learning tasks. However, as larger and larger data become acceptable for the current computational ma...
Abstract. Robustly estimating the state-transition probabilities of highorder Markov processes is an essential task in many applications such as natural language modeling or protei...
Abstract. This paper presents an empirical study on four techniques of language model adaptation, including a maximum a posteriori (MAP) method and three discriminative training mo...
Model checking is an automated technique for verifying that a system satisfies a set of required properties. Such properties are typically expressed as temporal logic formulas, in...