We develop an approach for a sparse representation for Gaussian Process (GP) models in order to overcome the limitations of GPs caused by large data sets. The method is based on a...
Abstract: We define events so as to reduce the number of events and decision variables needed for modeling batchscheduling problems such as described in [Westenberger and Kallrath ...
One of the important approaches for Knowledge discovery and Data mining is to estimate unobserved variables because latent variables can indicate hidden and specific properties o...
In life science, deeper understanding of biomolecular systems is acquired by computational modeling and analysis. For the modeling of several kinds of reaction networks, e.g. sign...
Abstract. The study of databases began with the design of efficient storage and data sharing techniques for large amount of data. This paper concerns the processing of imprecision ...