Probabilistic expert systemsbased on Bayesian networks(BNs)require initial specification both a qualitative graphical structure and quantitative assessmentof conditional probabili...
Abstract. An artificial system that achieves human-level performance on opendomain tasks must have a huge amount of knowledge about the world. We argue that the most feasible way t...
— This paper presents a novel stochastic link-layer channel model for IEEE 802.11 ad hoc networks. The model characterizes the variations of the channel service process in a non-...
This paper proposes a learning method of translation rules from parallel corpora. This method applies the maximum entropy principle to a probabilistic model of translation rules. ...
This paper presents a probabilistic model for sense disambiguation which chooses the best sense based on the conditional probability of sense paraphrases given a context. We use a...