Biclustering is a very popular method to identify hidden co-regulation patterns among genes. There are numerous biclustering algorithms designed to undertake this challenging task...
With the increasing availability of spatial data in many applications, spatial clustering and outlier detection has received a lot of attention in the database and data mining comm...
Recently there has been an increasing interest in developing regression models for large datasets that are both accurate and easy to interpret. Regressors that have these properti...
The spatial clustering of genes across different genomes has been used to study important problems in comparative genomics, from identification of operons to detection of homologo...
The goal of multi-objective clustering (MOC) is to decompose a dataset into similar groups maximizing multiple objectives in parallel. In this paper, we provide a methodology, arch...
Rachsuda Jiamthapthaksin, Christoph F. Eick, Ricar...