Most existing work on Privacy-Preserving Data Mining (PPDM) focus on enabling conventional data mining algorithms with the ability to run in a secure manner in a multi-party setti...
We describe a class of problems motivated by numerous real-world applications where there is a collection of objects that have both a cost and a value, but where some of those obj...
David L. Roberts, Charles L. Isbell, Michael L. Li...
Support Vector Machine has shown to have good performance in many practical classification settings. In this paper we propose, for multi-group classification, a biobjective optimi...
We study large-scale service systems with multiple customer classes and many statistically identical servers. The following question is addressed: How many servers are required (s...
Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surpris...