We address the problem of the combination of multiple data partitions, that we call a clustering ensemble. We use a recent clustering approach, known as Spectral Clustering, and th...
Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
This paper proposes a novel clustering analysis algorithm based on principal component analysis (PCA) and self-organizing maps (SOMs) for clustering the gene expression patterns. T...
This paper presents a system for graph clustering where users can visualize the clustering and give "hints" that help a computing method to find better solutions. Hints ...
Hierarchical metric-space clustering methods have been commonly used to organize proteomes into taxonomies. Consequently, it is often anticipated that hierarchical clustering can ...
Rui Mao, Weijia Xu, Neha Singh, Daniel P. Miranker