: We propose a set of statistical metrics for making a comprehensive, fair, and insightful evaluation of features, clustering algorithms, and distance measures in representative sa...
We present a Bayesian clustering algorithm for multivariate time series. A clustering is regarded as a probabilistic model in which the unknown auto-correlation structure of a tim...
Government agencies must often quickly organize and analyze large amounts of textual information, for example comments received as part of notice and comment rulemaking. Hierarchi...
This paper presents a simple but powerful extension of the maximum margin clustering (MMC) algorithm that optimizes multivariate performance measure specifically defined for clust...
Background: The sparse connectivity of protein-protein interaction data sets makes identification of functional modules challenging. The purpose of this study is to critically eva...