Evolutionary Combining of Basis Function Neural Networks for Classification. - César Hervás; Francisco José Martínez; Mariano Carbonero-Ruz; Cristóbal Romero 001; Juan Carlos Fernández 001 (IWINAC (1), 2007)

Multilogistic regression by means of evolutionary product-unit neural networks. - César Hervás-Martínez; Francisco J. Martínez-Estudillo; Mariano Carbonero-Ruz (Neural Networks, 2008)

Combined Projection and Kernel Basis Functions for Classification in Evolutionary Neural Networks. - Pedro Antonio Gutiérrez; César Hervás-Martínez; Mariano Carbonero-Ruz; Juan Carlos Fernández 001 (Innovations in Hybrid Intelligent Systems, 2008)

Combined projection and kernel basis functions for classification in evolutionary neural networks. - Pedro Antonio Gutiérrez; César Hervás; Mariano Carbonero-Ruz; Juan Carlos Fernández 001 (Neurocomputing, 2009)

Multilogistic Regression by Product Units. - Pedro Antonio Gutiérrez; César Hervás; Francisco J. Martínez-Estudillo; Mariano Carbonero-Ruz (Encyclopedia of Artificial Intelligence, 2009)

Evolutionary q-Gaussian Radial Basis Functions for Binary-Classification. - Francisco Fernández-Navarro; César Hervás-Martínez; Pedro Antonio Gutiérrez; Manuel Cruz-Ramírez; Mariano Carbonero-Ruz (HAIS (2), 2010)

Evolutionary Learning Using a Sensitivity-Accuracy Approach for Classification. - Javier Sánchez-Monedero; César Hervás-Martínez; Francisco J. Martínez-Estudillo; Mariano Carbonero-Ruz; M. C. Ramírez Moreno; Manuel Cruz-Ramírez (HAIS (2), 2010)

Numerical variable reconstruction from ordinal categories based on probability distributions. - Javier Sánchez-Monedero; Mariano Carbonero-Ruz; David Becerra-Alonso; Francisco J. Martínez-Estudillo; Pedro Antonio Gutiérrez; César Hervás-Martínez (ISDA, 2011)

A Hybrid Evolutionary Approach to Obtain Better Quality Classifiers. - David Becerra-Alonso; Mariano Carbonero-Ruz; Francisco J. Martínez-Estudillo; Alfonso C. Martínez-Estudillo (IWANN (2), 2011)

Evolutionary q-Gaussian radial basis function neural networks for multiclassification. - Francisco Fernández-Navarro; César Hervás-Martínez; Pedro Antonio Gutiérrez; Mariano Carbonero-Ruz (Neural Networks, 2011)

Evolutionary Extreme Learning Machine for Ordinal Regression. - David Becerra-Alonso; Mariano Carbonero-Ruz; Francisco J. Martínez-Estudillo; Alfonso C. Martínez-Estudillo (ICONIP (3), 2012)

A two-stage evolutionary algorithm based on sensitivity and accuracy for multi-class problems. - Pedro Antonio Gutiérrez; César Hervás-Martínez; Francisco J. Martínez-Estudillo; Mariano Carbonero-Ruz (Inf. Sci., 2012)

Learning from Label Proportions via an Iterative Weighting Scheme and Discriminant Analysis. - María Pérez-Ortiz 001; Pedro Antonio Gutiérrez; Mariano Carbonero-Ruz; César Hervás-Martínez (CAEPIA, 2016)

Adapting linear discriminant analysis to the paradigm of learning from label proportions. - María Pérez-Ortiz 001; Pedro Antonio Gutiérrez; Mariano Carbonero-Ruz; César Hervás-Martínez (SSCI, 2016)

Semi-supervised learning for ordinal Kernel Discriminant Analysis. - M. Pérez-Ortiz 001; Pedro Antonio Gutiérrez; Mariano Carbonero-Ruz; César Hervás-Martínez (Neural Networks, 2016)

A two dimensional accuracy-based measure for classification performance. - Mariano Carbonero-Ruz; Francisco J. Martínez-Estudillo; Francisco Fernández-Navarro; David Becerra-Alonso; Alfonso C. Martínez-Estudillo (Inf. Sci., 2017)

Global Sensitivity Estimates for Neural Network Classifiers. - Francisco Fernández-Navarro; Mariano Carbonero-Ruz; David Becerra-Alonso; Mercedes Torres-Jiménez (IEEE Trans. Neural Networks Learn. Syst., 2017)

A Preliminary Study of Diversity in Extreme Learning Machines Ensembles. - Carlos Perales-González; Mariano Carbonero-Ruz; David Becerra-Alonso; Francisco Fernández-Navarro (HAIS, 2018)

Multi-objective evolutionary optimization using the relationship between F 1 and accuracy metrics in classification tasks. - Juan Carlos Fernández 001; Mariano Carbonero-Ruz; Pedro Antonio Gutiérrez; César Hervás-Martínez (Appl. Intell., 2019)

Regularized ensemble neural networks models in the Extreme Learning Machine framework. - Carlos Perales-González; Mariano Carbonero-Ruz; David Becerra-Alonso; Javier Pérez-Rodríguez; Francisco Fernández-Navarro (Neurocomputing, 2019)

Negative correlation learning in the extreme learning machine framework. - Carlos Perales-González; Mariano Carbonero-Ruz; Javier Pérez-Rodríguez; David Becerra-Alonso; Francisco Fernández-Navarro (Neural Comput. Appl., 2020)

Negative Correlation Hidden Layer for the Extreme Learning Machine. - Carlos Perales-González; Francisco Fernández-Navarro; Javier Pérez-Rodríguez; Mariano Carbonero-Ruz (Appl. Soft Comput., 2021)

An experimental study on diversification in portfolio optimization. - Luisa Martínez-Nieto; Francisco Fernández-Navarro; Mariano Carbonero-Ruz; Teresa Montero-Romero (Expert Syst. Appl., 2021)

Global Negative Correlation Learning: A Unified Framework for Global Optimization of Ensemble Models. - Carlos Perales-González; Francisco Fernández-Navarro; Mariano Carbonero-Ruz; Javier Pérez-Rodríguez (IEEE Trans. Neural Networks Learn. Syst., 2022)

A multi-class classification model with parametrized target outputs for randomized-based feedforward neural networks. - Antonio Manuel Durán-Rosal; Aggeo Durán-Fernández; Francisco Fernández-Navarro; Mariano Carbonero-Ruz (Appl. Soft Comput., 2023)

Enhancing financial time series forecasting through topological data analysis. - Luiz Carlos de Jesus Jr.; Francisco Fernández-Navarro; Mariano Carbonero-Ruz (Neural Comput. Appl., 2025)