A comparative study of parallel metaheuristics executed in grid environments is proposed, having as case study a genetic algorithm, a simulated annealing algorithm and a random se...
We consider the problem of clustering in its most basic form where only a local metric on the data space is given. No parametric statistical model is assumed, and the number of cl...
Background: Random forest, an ensemble based supervised machine learning algorithm, is used to predict the SCOP structural classification for a target structure, based on the simi...
We present a new approach for an average-case analysis of algorithms and data structures that supports a non-uniform distribution of the inputs and is based on the maximum likelih...
Bayesian networks (BN) constitute a useful tool to model the joint distribution of a set of random variables of interest. To deal with the problem of learning sensible BN models fr...