Classical clustering algorithms are based on the concept that a cluster center is a single point. Clusters which are not compact around a single point are not candidates for class...
Identification of distinct clusters of documents in text collections has traditionally been addressed by making the assumption that the data instances can only be represented by ...
Levent Bolelli, Seyda Ertekin, Ding Zhou, C. Lee G...
Numerous mesh algorithms such as parametrization, radiosity, and collision detection require the decomposition of meshes into a series of clusters. In this paper we present two no...
This paper is concerned with transductive learning. Although transduction appears to be an easier task than induction, there have not been many provably useful algorithms and boun...
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...