Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Abstract—In this paper we demonstrate the inherent robustness of minimum distance estimator that makes it a potentially powerful tool for parameter estimation in gene expression ...
This paper will discuss high performance clustering from a series of critical topics: architectural design, system software infrastructure, and programming environment. This will ...
David A. Bader, Arthur B. Maccabe, Jason R. Mastal...
Background: Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to di...
With increasing demands for high performance by embedded systems, especially by digital signal processing applications, embedded processors must increase available instruction lev...