Clustering data in high dimensions is believed to be a hard problem in general. A number of efficient clustering algorithms developed in recent years address this problem by proje...
Kamalika Chaudhuri, Sham M. Kakade, Karen Livescu,...
The ParaStation communication fabric provides a high-speed communicationnetwork with user-levelaccess to enable e cientparallel computing on workstation clusters. The architecture...
Thomas M. Warschko, Joachim M. Blum, Walter F. Tic...
Many clustering algorithms fail when dealing with high dimensional data. Principal component analysis (PCA) is a popular dimensionality reduction algorithm. However, it assumes a ...
With the success of open source software projects, such as Apache and Mozilla, comes the opportunity to study the development process. In this paper, we present StarGate: a novel ...
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...