In this paper, we deal with the problem of Deep Belief Networks (DBNs) parameters fine-tuning by means of a fast meta-heuristic approach named Harmony Search (HS). Although such deep learning-based technique has been widely ...

In this paper, we deal with the problem of Deep Belief Networks (DBNs) parameters fine-tuning by means of a fast meta-heuristic approach named Harmony Search (HS). Although such deep learning-based technique has been widely ...

In the last few years, metaheuristic-driven optimization has been employed to address deep belief network (DBN) model selection, since it provides simple and elegant solutions in a wide range of applications. In this work, ...

Técnicas para seleção de características tem sido amplamente estudadas pela comunidade científica de reconhecimento de padrões e areas afins, dado que o problema de encontrar o subconjunto das características que maximiza ...

Deep learning techniques have been paramount in the last years, mainly due to their outstanding results in a number of applications. In this paper, we address the issue of fine-tuning parameters of Deep Belief Networks by ...

In this paper we propose an improved Harmony Search (HS) version inspired in the tonal variation of jazz musical improvisation. To evaluate our approach we considered two well-known problems, a Constraint Satisfaction ...