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An evolutionary algorithm of linear complexity: application to training of de...
The performance of deep neural networks, such as Deep Belief Networks formed by Restricted Boltzmann Machines (RBMs), strongly depends on their training, which is the process of... -
Comparison of Parallel Versions of SA and GA for Optimizing the Performance o...
Deep learning (DL) is playing an increasingly important role in our lives. It has already made a huge impact in areas, such as cancer diagnosis, precision medicine, self-driving... -
Efficient training of deep learning models through improved adaptive sampling
Training of Deep Neural Networks (DNNs) is very computationally demanding and resources are typically spent on training-instances that do not provide the most benefit to a... -
Spatio-temporal interpolation of rainfall data in western Mexico
One of the most common problems related to meteorological information is the missing registers. This lack of data generates uncertainties in the analysis of climate, hydrology,... -
Valley Classification using Convolutional Neural Network and a Geomorphons Map
Geomorphological classification serves as a valuable tool for comprehending the origin and evolution of landscapes, as well as for making informed decisions regarding...
