In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...
Linear System Identification yields a nominal model parameter, which minimizes a specific criterion based on the single inputoutput data set. Here we investigate the utility of va...
Background: Physical maps are the substrate of genome sequencing and map-based cloning and their construction relies on the accurate assembly of BAC clones into large contigs that...
Zeev Frenkel, Etienne Paux, David I. Mester, Cathe...
In this paper, we address a unique problem in Chinese language processing and report on our study on extending a Chinese thesaurus with region-specific words, mostly from the fina...
Abstract. Usage of combinatorial testing is wide spreading as an effective technique to reveal unintended feature interaction inside a given system. To this aim, test cases are con...