Clusters of computers have emerged as cost-effective parallel and/or distributed computing systems for computationally intensive tasks. Normally, clusters are composed of high per...
Isaac D. Scherson, Daniel S. Valencia, Enrique Cau...
We present a novel multiscale clustering algorithm inspired by algebraic multigrid techniques. Our method begins with assembling data points according to local similarities. It us...
This paper proposes a novel nonparametric clustering algorithm capable of identifying shape-free clusters. This algorithm is based on a nonparametric estimation of the normalized ...
Chaolin Zhang, Xuegong Zhang, Michael Q. Zhang, Ya...
Detecting local clustered anomalies is an intricate problem for many existing anomaly detection methods. Distance-based and density-based methods are inherently restricted by their...
Mean shift is a popular approach for data clustering, however, the high computational complexity of the mean shift procedure limits its practical applications in high dimensional ...