Oscar Gabriel Reyes Pupo

According to our database, Oscar Gabriel Reyes Pupo authored at least 19 papers between 2012 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Performing Cancer Diagnosis via an Isoform Expression Ranking-based LSTM Model.

Oscar Gabriel Reyes Pupo, Eduardo Pérez

ACM Trans. Intell. Syst. Technol., December, 2023

Performing Melanoma Diagnosis by an Effective Multi-view Convolutional Network Architecture.

Eduardo Pérez, Oscar Gabriel Reyes Pupo

Int. J. Comput. Vis., 2023

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 multi-target regression via gene expression programming-based ensemble models.

Jose M. Moyano, Oscar Gabriel Reyes Pupo, Habib M. Fardoun, Sebastián Ventura

Neurocomputing, 2021

2020

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

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 Methodology for Analyzing Dysregulation in Splicing Machinery: An Application in Cancer Diagnosis.

Oscar Gabriel Reyes Pupo, Raúl M. Luque, Justo Castaño, Sebastián Ventura

Proceedings of the 32nd IEEE International Symposium on Computer-Based Medical Systems, 2019

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

Statistical comparisons of active learning strategies over multiple datasets.

Oscar Gabriel Reyes Pupo, Abdulrahman H. Altalhi, Sebastián Ventura

Knowl. Based Syst., 2018

Effective active learning strategy for multi-label learning.

Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura

Neurocomputing, 2018

A locally weighted learning method based on a data gravitation model for multi-target regression.

Oscar Gabriel Reyes Pupo, Alberto Cano, Habib M. Fardoun, Sebastián Ventura

Int. J. Comput. Intell. Syst., 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 gene expression programming method for multi-target regression.

Oscar Gabriel Reyes Pupo, Jose María Moyano Murillo, José María Luna, Sebastián Ventura

Proceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications, 2018

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

Effective lazy learning algorithm based on a data gravitation model for multi-label learning.

Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura

Inf. Sci., 2016

2015

Scalable extensions of the ReliefF algorithm for weighting and selecting features on the multi-label learning context.

Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura

Neurocomputing, 2015

2014

Evolutionary feature weighting to improve the performance of multi-label lazy algorithms.

Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura

Integr. Comput. Aided Eng., 2014

2013

ReliefF-ML: An Extension of ReliefF Algorithm to Multi-label Learning.

Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura Soto

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2013

2012

Learning similarity metric to improve the performance of lazy multi-label ranking algorithms.

Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura

Proceedings of the 12th International Conference on Intelligent Systems Design and Applications, 2012