This paper presents a data oriented approach to modeling the complex computing systems, in which an ensemble of correlation models are discovered to represent the system status. I...
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
The two main challenges typically associated with mining data streams are concept drift and data contamination. To address these challenges, we seek learning techniques and models ...
Background: While the pairwise alignments produced by sequence similarity searches are a powerful tool for identifying homologous proteins - proteins that share a common ancestor ...
Michael L. Sierk, Michael E. Smoot, Ellen J. Bass,...
Background: Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologou...