This paper investigates the design of parallel algorithmic strategies that address the efficient use of both, memory hierarchies within each processor and a multilevel clustered ...
Frank K. H. A. Dehne, Stefano Mardegan, Andrea Pie...
Active data clustering is a novel technique for clustering of proximity data which utilizes principles from sequential experiment design in order to interleave data generation and...
The goal of this paper is to further investigate the extreme behaviour of the proportional membership model (FCPM) in contrast to the central tendency of fuzzy c-means (FCM). A dat...
Susana Nascimento, Boris Mirkin, Fernando Moura-Pi...
Background: The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both indiv...
Curtis Huttenhower, Avi I. Flamholz, Jessica N. La...
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...