Model order selection and cue combination are both difficult open problems in the area of clustering. In this work we build upon stability-based approaches to develop a new method...
Andrew Rabinovich, Serge Belongie, Tilman Lange, J...
A straightforward and efficient way to discover clustering tendencies in data using a recently proposed Maximum Variance Clustering algorithm is proposed. The approach shares the ...
An original method is proposed for spatial cluster detection of case event data. A selection order and the distance from the nearest neighbour are attributed to each point, once p...
In comparative genomics, various combinatorial models can be used to specify gene clusters — groups of genes that are co-located in a set of genomes. Several approaches have been...
Abstract. Noise significantly affects cluster quality. Conventional clustering methods hardly detect clusters in a data set containing a large amount of noise. Projected clusterin...
Jiuyong Li, Xiaodi Huang, Clinton Selke, Jianming ...