A linear multivariate measurement error model AX = B is considered. The errors in A B are row-wise finite dependent, and within each row, the errors may be correlated. Some of th...
Alexander Kukush, Ivan Markovsky, Sabine Van Huffe...
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
We employ Maximum Entropy model to conduct sub-tree alignment between bilingual phrasal structure trees. Various lexical and structural knowledge is explored to measure the syntac...
Background: Recent discoveries of a large variety of important roles for non-coding RNAs (ncRNAs) have been reported by numerous researchers. In order to analyze ncRNAs by kernel ...
Several advanced applications, such as those dealing with the Web, need to handle data whose structure is not known a-priori. Such requirement severely limits the applicability of ...