—The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such...
The recent years have witnessed a surge of interests of semi-supervised clustering methods, which aim to cluster the data set under the guidance of some supervisory information. U...
We propose a novel semi-supervised clustering method for the task of gene regulatory module discovery. The technique uses data on dna binding as prior knowledge to guide the proces...
Abstract. Constrained clustering investigates how to incorporate domain knowledge in the clustering process. The domain knowledge takes the form of constraints that must hold on th...
This paper introduces a semi-supervised distance metric learning algorithm which uses pair-wise equivalence (similarity and dissimilarity) constraints to improve the original dist...