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Quaternion-based Deep Belief Networks fine-tuning
(Elsevier B.V., 2017-11-01)
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 ...
Fine-tuning Deep Belief Networks using Harmony Search
(Elsevier B.V., 2016-09-01)
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 ...
A simple method for choosing the parameters of a two degree-of-freedom tuned vibration absorber
(Academic Press Ltd Elsevier B.V. Ltd, 2012-10-08)
In this paper a new method for choosing the parameters of a Two degree-of-freedom (dof) tuned vibration absorber (TVA) with translational and rotational degrees of freedom is described. The dynamic stiffness approach is ...
A simple method for choosing the parameters of a two degree-of-freedom tuned vibration absorber
(Academic Press Ltd Elsevier B.V. Ltd, 2012-10-08)
In this paper a new method for choosing the parameters of a Two degree-of-freedom (dof) tuned vibration absorber (TVA) with translational and rotational degrees of freedom is described. The dynamic stiffness approach is ...
Meta-learning recommendation of default hyper-parameter values for SVMs in classifications tasks
(University of PortoPorto, 2015-09)
Machine learning algorithms have been investigated in several scenarios, one of them is the data classification. The predictive performance of the models induced by these algorithms is usually strongly affected by the ...
Isomerization and Redox Tuning: Reorganizing the Maya Blue Puzzle from Synthetic, Spectral, and Electrochemical Issues
A new approach to describe the composition of Maya blue (MB), an ancient organic-inorganic hybrid material, is presented. It is based on the analysis of attenuated total reflection-Fourier transform infrared (ATR-FTIR), ...
Fine-Tuning Infinity Restricted Boltzmann Machines
(Ieee, 2017-01-01)
Restricted Boltzmann Machines (RBMs) have received special attention in the last decade due to their outstanding results in number of applications, such as face and human motion recognition, and collaborative filtering, ...