In this study, we formalize a multi-focal learning problem, where training data are partitioned into several different focal groups and the prediction model will be learned within...
Yong Ge, Hui Xiong, Wenjun Zhou, Ramendra K. Sahoo...
Economic resource allocation in Application Layer Networks (such as Grids) is critical to allow applications and users to effectively exploit computational and data infrastructure...
Werner Streitberger, Michael Reinicke, Torsten Eym...
Privacy-preserving data mining (PPDM) is an emergent research area that addresses the incorporation of privacy preserving concerns to data mining techniques. In this paper we prop...
Evaluation and applicability of many database techniques, ranging from access methods, histograms, and optimization strategies to data normalization and mining, crucially depend o...
This paper describes an approach to real-time decisionmaking for quality of service based scheduling of distributed asynchronous data replication. The proposed approach addresses ...