Computing methods that allow the efficient and accurate processing of experimentally gathered data play a crucial role in biological research. The aim of this paper is to present a...
The Bayesian framework of learning from positive noise-free examples derived by Muggleton [12] is extended to learning functional hypotheses from positive examples containing norma...
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...
Abstract— This paper presents an approach to create topological maps from geometric maps obtained with a mobile robot in an indoor-environment using range data. Our approach util...
Schlumberger RPS successfully applies software measurement to support their software development projects. It is proposed that the success of their measurement practices is mainly...