A new stochastic clustering algorithm is introduced that aims to locate all the local minima of a multidimensional continuous and differentiable function inside a bounded domain. ...
Clustering methods for data-mining problems must be extremely scalable. In addition, several data mining applications demand that the clusters obtained be balanced, i.e., be of ap...
A common technique used to minimize I/O in data intensive applications is data declustering over parallel servers. This technique involves distributing data among several disks so...
Hakan Ferhatosmanoglu, Ali Saman Tosun, Guadalupe ...
Background: We develop a Bayesian method based on MCMC for estimating the relative rates of pericentric and paracentric inversions from marker data from two species. The method al...
Grids allow large scale resource-sharing across different administrative domains. Those diverse resources are likely to join or quit the Grid at any moment or possibly to break dow...
Francesc Guim, Ivan Rodero, M. Tomas, Julita Corba...