In spatial clustering, the scale of spatial data is usually very large. Spatial clustering algorithms need high performance, good scalability, and are able to deal with noise and ...
We present a fast method that adaptively approximates large-scale functional scattered data sets with hierarchical B-splines. The scheme is memory efficient, easy to implement an...
Abstract. Sensor networks represent a non traditional source of information, as readings generated by sensors flow continuously, leading to an infinite stream of data. Traditiona...
Background: In recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms suc...
Yi Lu, Shiyong Lu, Farshad Fotouhi, Youping Deng, ...
We propose a novel hierarchical clustering algorithm for data-sets in which only pairwise distances between the points are provided. The classical Hungarian method is an efficient...