Portal de Periódicos da CAPES

Artigo Produção Nacional Revisado por pares

BIBTEX RIS

Model selection for Discriminative Restricted Boltzmann Machines through meta-heuristic techniques

2015; Elsevier BV; Volume: 9; Linguagem: Inglês

10.1016/j.jocs.2015.04.014

1877-7511

João Paulo Papa, Gustavo Henrique de Rosa, Aparecido Nilceu Marana, Walter J. Scheirer, David Cox,

Neural Networks and Applications

Discriminative learning of Restricted Boltzmann Machines has been recently introduced as an alternative to provide a self-contained approach for both unsupervised feature learning and classification purposes. However, one of the main problems faced by researchers interested in such approach concerns with a proper selection of its parameters, which play an important role in its final performance. In this paper, we introduced some meta-heuristic techniques for this purpose, as well as we showed they can be more accurate than a random search, which is commonly used technique in several works.