We describe a generative probabilistic model of natural language, which we call HBG, that takes advantage of detailed linguistic information to resolve ambiguity. HBG incorporates...
Ezra Black, Frederick Jelinek, John D. Lafferty, D...
In this paper, we propose a formal analysis approach to estimate the expected (average) data cache access time of an application across all possible program inputs. Towards this g...
This paper proposes a method for identifying protein names in biomedical texts with an emphasis on detecting protein name boundaries. We use a probabilistic model which exploits s...
We propose a new discriminative framework, namely Hidden Dynamic Conditional Random Fields (HDCRFs), for building probabilistic models which can capture both internal and external...
In probabilistic reasoning, the problems of existence and identity are important to many different queries; for example, the probability that something that fits some description...