This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
The primary aim of most data mining algorithms is to facilitate the discovery of concise and interpretable information from large amounts of data. However, many of the current for...
In this work, we investigate various specification languages and their relation to Casl, the recently developed Common Algebraic Specification Language. In particular, we consider...
traction and information hiding K. RUSTAN M. LEINO and GREG NELSON Compaq Systems Research Center er describes an approach for verifying programs in the presence of data abstractio...
There are numerous applications where there is a need to rapidly infer a story about a given subject from a given set of potentially heterogeneous data sources. In this paper, we f...
Marat Fayzullin, V. S. Subrahmanian, Massimiliano ...