We present two algorithms for learning large-scale gene regulatory networks from microarray data: a modified informationtheory-based Bayesian network algorithm and a modified asso...
Zan Huang, Jiexun Li, Hua Su, George S. Watts, Hsi...
Nonparametric neighborhood methods for learning entail estimation of class conditional probabilities based on relative frequencies of samples that are "near-neighbors" of...
This paper presents an approach for the integration of domain related elements and operational semantics into collaborative environments based on visual languages. This integratio...
Niels Pinkwart, Heinz Ulrich Hoppe, Katrin Ga&szli...
An advanced Business Game is presented in the paper, built on the methodology of System Dynamics. It can be used for cognitive learning and knowledge transmission in schools and U...
Abstract. We introduce a nonparametric model for sensitivity estimation which relies on generating points similar to the prediction point using its k nearest neighbors. Unlike most...