- Clustering plays an indispensable role for data analysis. Many clustering algorithms have been developed. However, most of them suffer either poor performance of unsupervised lea...
We examine methods for clustering in high dimensions. In the first part of the paper, we perform an experimental comparison between three batch clustering algorithms: the Expectat...
Hartigan's method for k-means clustering is the following greedy heuristic: select a point, and optimally reassign it. This paper develops two other formulations of the heuri...
networking with a layer 2 abstraction provides a powerful model for virtualized wide-area distributed computing resources, including for high performance computing (HPC) on collec...
Lei Xia, Zheng Cui, John R. Lange, Yuan Tang, Pete...
This article provides a simple and general way for defining the recovery rate of clustering algorithms using a given family of old clusters for evaluating the performance of the a...