Clustering methods usually require to know the best number of clusters, or another parameter, e.g. a threshold, which is not ever easy to provide. This paper proposes a new graph-b...
Abstract. Clustering algorithms based on a matrix of pairwise similarities (kernel matrix) for the data are widely known and used, a particularly popular class being spectral clust...
We propose an unsupervised methodology using independent component analysis (ICA) to cluster genes from DNA microarray data. Based on an ICA mixture model of genomic expression pa...
In this paper, we investigate the maximization of the amount of gathered data in a clustered wireless sensor network (WSN). The amount of gathered data is maximized by (1) choosing...
—In this paper, we study the node clustering problem in UnderWater Sensor Networks (UWSNs). We formulate the problem into a cluster-centric cost-based optimization problem with a...