Learning similarity metric to improve the performance of lazy multi-label ranking algorithms. - Oscar Gabriel Reyes Pupo; Carlos Morell 001; Sebastián Ventura (ISDA, 2012)

ReliefF-ML: An Extension of ReliefF Algorithm to Multi-label Learning. - Oscar Gabriel Reyes Pupo; Carlos Morell 001; Sebastián Ventura Soto (CIARP (2), 2013)

Evolutionary feature weighting to improve the performance of multi-label lazy algorithms. - Oscar Gabriel Reyes Pupo; Carlos Morell 001; Sebastián Ventura (Integr. Comput. Aided Eng., 2014)

Scalable extensions of the ReliefF algorithm for weighting and selecting features on the multi-label learning context. - Oscar Gabriel Reyes Pupo; Carlos Morell 001; Sebastián Ventura (Neurocomputing, 2015)

Effective lazy learning algorithm based on a data gravitation model for multi-label learning. - Oscar Gabriel Reyes Pupo; Carlos Morell 001; Sebastián Ventura (Inf. Sci., 2016)

JCLAL: A Java Framework for Active Learning. - Oscar Gabriel Reyes Pupo; Eduardo Pérez; María del Carmen Rodríguez-Hernández; Habib M. Fardoun; Sebastián Ventura (J. Mach. Learn. Res., 2016)

A gene expression programming method for multi-target regression. - Oscar Gabriel Reyes Pupo; Jose María Moyano Murillo; José María Luna; Sebastián Ventura (LOPAL, 2018)

An ensemble-based method for the selection of instances in the multi-target regression problem. - Oscar Gabriel Reyes Pupo; Habib M. Fardoun; Sebastián Ventura (Integr. Comput. Aided Eng., 2018)

A locally weighted learning method based on a data gravitation model for multi-target regression. - Oscar Gabriel Reyes Pupo; Alberto Cano 001; Habib M. Fardoun; Sebastián Ventura (Int. J. Comput. Intell. Syst., 2018)

Effective active learning strategy for multi-label learning. - Oscar Gabriel Reyes Pupo; Carlos Morell 001; Sebastián Ventura (Neurocomputing, 2018)

Statistical comparisons of active learning strategies over multiple datasets. - Oscar Gabriel Reyes Pupo; Abdulrahman H. Altalhi; Sebastián Ventura (Knowl. Based Syst., 2018)

Evolutionary Strategy to Perform Batch-Mode Active Learning on Multi-Label Data. - Oscar Gabriel Reyes Pupo; Sebastián Ventura (ACM Trans. Intell. Syst. Technol., 2018)

A Supervised Methodology for Analyzing Dysregulation in Splicing Machinery: An Application in Cancer Diagnosis. - Oscar Gabriel Reyes Pupo; Raúl M. Luque; Justo Castaño; Sebastián Ventura (CBMS, 2019)

Performing Multi-Target Regression via a Parameter Sharing-Based Deep Network. - Oscar Gabriel Reyes Pupo; Sebastián Ventura (Int. J. Neural Syst., 2019)

A supervised machine learning-based methodology for analyzing dysregulation in splicing machinery: An application in cancer diagnosis. - Oscar Gabriel Reyes Pupo; Eduardo Pérez; Raúl M. Luque; Justo Castaño; Sebastián Ventura (Artif. Intell. Medicine, 2020)

Performing multi-target regression via gene expression programming-based ensemble models. - Jose M. Moyano; Oscar Gabriel Reyes Pupo; Habib M. Fardoun; Sebastián Ventura (Neurocomputing, 2021)

Convolutional neural networks for the automatic diagnosis of melanoma: An extensive experimental study. - Eduardo Pérez; Oscar Gabriel Reyes Pupo; Sebastián Ventura (Medical Image Anal., 2021)

Performing Melanoma Diagnosis by an Effective Multi-view Convolutional Network Architecture. - Eduardo Pérez; Oscar Gabriel Reyes Pupo (Int. J. Comput. Vis., 2023)

Performing Cancer Diagnosis via an Isoform Expression Ranking-based LSTM Model. - Oscar Gabriel Reyes Pupo; Eduardo Pérez (ACM Trans. Intell. Syst. Technol., 2023)