We present a theoretical study on the discriminative clustering framework, recently proposed for simultaneous subspace selection via linear discriminant analysis (LDA) and cluster...
—The rapid burgeoning of available protein data makes the use of clustering within families of proteins increasingly important, the challenge is to identify subfamilies of evolut...
Abdellali Kelil, Shengrui Wang, Ryszard Brzezinski
Sensor networks usually generate continuous stream of data over time. Clustering sensor data as a core task of mining sensor data plays an essential role in analytical application...
Amirhosein Taherkordi, Reza Mohammadi, Frank Elias...
Abstract. We present the first (to our knowledge) approximation algorithm for tensor clustering—a powerful generalization to basic 1D clustering. Tensors are increasingly common...
This paper addresses the problem of improving quality of security for real-time parallel applications on heterogeneous clusters. We propose a new security- and heterogeneity-drive...