A genetic algorithm-based clustering technique, called GA-clustering, is proposed in this article. The searching capability of genetic algorithms is exploited in order to search f...
We propose a new approach to semi-supervised clustering that utilizes boosting to simultaneously learn both a similarity measure and a clustering of the data from given instancele...
In the past decades, many clustering algorithms have been proposed for the analysis of gene expression data, but little guidance is available to help choose among them. Given the ...
We propose a method of clustering images that combines algorithmic and human input. An algorithm provides us with pairwise image similarities. We then actively obtain selected, mo...
We propose a novel multivariate uniformity criterion for testing uniformity of point density in an arbitrary dimensional point pattern . An unsupervised, nonparametric data cluste...