Abstract. Constrained clustering investigates how to incorporate domain knowledge in the clustering process. The domain knowledge takes the form of constraints that must hold on th...
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
This paper addresses a purely software-based solution to the multiprocessor cache coherence problem by structuring an operating system to provide for the coherence of its own data...
Affordable transparent clustering solutions to scale non-HPC applications on commodity clusters (such as Terracotta) are emerging for Java Virtual Machines (JVMs). Working in this ...