Background: The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both indiv...
Curtis Huttenhower, Avi I. Flamholz, Jessica N. La...
Model-based clustering exploits finite mixture models for detecting group in a data set. It provides a sound statistical framework which can address some important issues, such as...
Permutation ambiguity is an inherent limitation in independent component analysis, which is a bottleneck in frequency-domain methods of convolutive source separation. In this pape...
We present a new method for spectral clustering with paired data based on kernel canonical correlation analysis, called correlational spectral clustering. Paired data are common i...
Speaker clustering is the task of grouping a set of speech utterances into speaker-specific classes. The basic techniques for solving this task are similar to those used for spea...