The popular K-means clustering partitions a data set by minimizing a sum-of-squares cost function. A coordinate descend method is then used to nd local minima. In this paper we sh...
Hongyuan Zha, Xiaofeng He, Chris H. Q. Ding, Ming ...
In previous work on "transformed mixtures of Gaussians" and "transformed hidden Markov models", we showed how the EM algorithm in a discrete latent variable mo...
Dominant sets are a new graph-theoretic concept that has proven to be relevant in pairwise data clustering problems, such as image segmentation. They generalize the notion of a ma...
Abstract. In this article we present the results obtained from the execution of a commercial Computational Fluid Dynamics program on a cluster of personal computers. The communicat...
- Ever-increasing demands of space missions for data returns from their limited processing and communications resources have made the traditional approach of data gathering, data c...
Rajagopal Subramaniyan, Vikas Aggarwal, Adam Jacob...