Traditional binary hypothesis testing relies on the precise knowledge of the probability density of an observed random vector conditioned on each hypothesis. However, for many app...
Conditional deduction in binary logic basically consists of deriving new statements from an existing set of statements and conditional rules. Modus Ponens, which is the classical e...
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...
The dependency propagation problem is to determine, given a view defined on data sources and a set of dependencies on the sources, whether another dependency is guaranteed to hold...
Wenfei Fan, Shuai Ma, Yanli Hu, Jie Liu, Yinghui W...
Abstract. Pattern-based model-to-model transformation is a new approach for specifying transformations in a declarative, relational and formal style. The language relies on pattern...