Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how to encode constraints into spectral clustering rem...
Clusters are now composed of non-uniform nodes with different CPUs, disks or network cards so that customers can adapt the cluster configuration to the changing technologies and t...
Tobias Mayr, Philippe Bonnet, Johannes Gehrke, Pra...
—Secret sharing and erasure coding-based approaches have been used in distributed storage systems to ensure the confidentiality, integrity, and availability of critical informati...
Manghui Tu, Peng Li, I-Ling Yen, Bhavani M. Thurai...
—In this paper, we explore a new data mining capability that involves mining path traversal patterns in a distributed information-providing environment where documents or objects...
Probabilistic mixture models are used for a broad range of data analysis tasks such as clustering, classification, predictive modeling, etc. Due to their inherent probabilistic na...