Estimating the Maximum Power Delivered by Concentrating Photovoltaics Technology Through Atmospheric Conditions Using a Differential Evolution Approach. - Cristóbal J. Carmona; Francisco Javier Pulgar; Antonio Jesús Rivera Rivas; María José del Jesus; Jorge Aguilera 001 (HAIS, 2016)

On the Impact of Imbalanced Data in Convolutional Neural Networks Performance. - Francisco Javier Pulgar; Antonio J. Rivera; Francisco Charte; María José del Jesus (HAIS, 2017)

A Transformation Approach Towards Big Data Multilabel Decision Trees. - Antonio Jesús Rivera Rivas; Francisco Charte Ojeda; Francisco Javier Pulgar; María José del Jesus (IWANN (1), 2017)

MEFASD-BD: Multi-objective evolutionary fuzzy algorithm for subgroup discovery in big data environments - A MapReduce solution. - Francisco Javier Pulgar; Antonio Jesús Rivera Rivas; María Dolores Pérez-Godoy; Pedro González 001; Cristóbal J. Carmona; María José del Jesus (Knowl. Based Syst., 2017)

A First Approach to Face Dimensionality Reduction Through Denoising Autoencoders. - Francisco Javier Pulgar; Francisco Charte; Antonio J. Rivera; María José del Jesus (IDEAL (1), 2018)

AEkNN: An AutoEncoder kNN-Based Classifier With Built-in Dimensionality Reduction. - Francisco Javier Pulgar; Francisco Charte; Antonio J. Rivera; María José del Jesus (Int. J. Comput. Intell. Syst., 2019)

Choosing the proper autoencoder for feature fusion based on data complexity and classifiers: Analysis, tips and guidelines. - Francisco Javier Pulgar; Francisco Charte; Antonio J. Rivera; María José del Jesus (Inf. Fusion, 2020)

ClEnDAE: A classifier based on ensembles with built-in dimensionality reduction through denoising autoencoders. - Francisco Javier Pulgar; Francisco Charte; Antonio J. Rivera; María José del Jesus (Inf. Sci., 2021)