Learning Bayesian network structure from large-scale data sets, without any expertspecified ordering of variables, remains a difficult problem. We propose systematic improvements ...
The problem of assigning structural properties of a linear system through sensor selection is, for a given pair (A, B), to find an output pair (C, D) such that the resulting syst...
Naive Bayesian classifiers have been very successful in attribute-value representations. However, it is not clear how the decomposition of the probability distributions on attribu...
We examine scattered hairpins, which are structures formed when a single strand of nucleotides folds into a partially hybridized stem and a loop. To specify different classes of h...
The rapid developing area of compressed sensing suggests that a sparse vector lying in a high dimensional space can be accurately and efficiently recovered from only a small set of...