An analysis method for specialization of imperative programs is described in this paper. This analysis is an inter-procedural data flow method operating on control flow graphs and...
Cyclic definitions are often prohibited in terminological knowledge representation languages because, from a theoretical point of view, their semantics is not clear and, from a pr...
Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...
Many temporal processes can be naturally modeled as a stochastic system that evolves continuously over time. The representation language of continuous-time Bayesian networks allow...
We present an approximation to the Bayesian hierarchical PitmanYor process language model which maintains the power law distribution over word tokens, while not requiring a comput...