— Clustering is a pivotal building block in many data mining applications and in machine learning in general. Most clustering algorithms in the literature pertain to off-line (or...
Steven Young, Itamar Arel, Thomas P. Karnowski, De...
In distributed data mining models, adopting a flat node distribution model can affect scalability. To address the problem of modularity, flexibility and scalability, we propose...
Users perceive varying levels of utility for each different job completed by the cluster. Therefore, there is a need for existing cluster Resource Management Systems (RMS) to prov...
Current clustering techniques are able to identify arbitrarily shaped clusters in the presence of noise, but depend on carefully chosen model parameters. The choice of model param...
One of the advantages in virtualized computing clusters compared to traditional shared HPC environments is their ability to accommodate user-specific system customization. Howeve...