Restricted Boltzmann Machines achieved notorious popularity in the scientific community in the last decade due to outstanding results in a wide range of applications and also for providing the required mechanisms to build ...

Restricted Boltzmann Machines achieved notorious popularity in the scientific community in the last decade due to outstanding results in a wide range of applications and also for providing the required mechanisms to build ...

Nowadays, spam detection has been one of the foremost machine learning-oriented applications in the context of security in computer networks. In this work, we propose to learn intrinsic properties of e-mail messages by ...

Deep learning techniques have been paramount in the last years, mainly due to their outstanding results in a number of applications, that range from speech recognition to face-based user identification. Despite other ...

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 ...

Deep learning techniques have been studied extensively in the last years, due to its good results related to essential tasks on a large range of applications, such as speech and face recognition, as well as objects ...

Technology has been nurturing a wide range of applications in the past decades, assisting humans in automating some of their daily tasks. Nevertheless, more advanced technology systems also expose some potential flaws, ...

Currently, Parkinson’s Disease (PD) has no cure or accurate diagnosis, reaching approximately 60,000 new cases yearly and worldwide, being more often in the elderly population. Its main symptoms can not be easily uncorrelated ...

Deep learning architectures have been widely fostered throughout the last years, being used in a wide range of applications, such as object recognition, image reconstruction, and signal processing. Nevertheless, such models ...