Oscar Gabriel Reyes Pupo

19 papers B 1C 1Journal 15Unranked 2
YearRankTypeTitle / Venue / Authors
2023 J jnl
Performing Cancer Diagnosis via an Isoform Expression Ranking-based LSTM Model.
ACM Trans. Intell. Syst. Technol.
Oscar Gabriel Reyes Pupo, Eduardo Pérez
2023 J jnl
Performing Melanoma Diagnosis by an Effective Multi-view Convolutional Network Architecture.
Int. J. Comput. Vis.
Eduardo Pérez, Oscar Gabriel Reyes Pupo
2021 J jnl
Convolutional neural networks for the automatic diagnosis of melanoma: An extensive experimental study.
Medical Image Anal.
Eduardo Pérez, Oscar Gabriel Reyes Pupo, Sebastián Ventura
2021 J jnl
Performing multi-target regression via gene expression programming-based ensemble models.
Neurocomputing
Jose M. Moyano, Oscar Gabriel Reyes Pupo, Habib M. Fardoun, Sebastián Ventura
2020 J jnl
A supervised machine learning-based methodology for analyzing dysregulation in splicing machinery: An application in cancer diagnosis.
Artif. Intell. Medicine
Oscar Gabriel Reyes Pupo, Eduardo Pérez, Raúl M. Luque, Justo Castaño, Sebastián Ventura
2019 B conf
A Supervised Methodology for Analyzing Dysregulation in Splicing Machinery: An Application in Cancer Diagnosis.
CBMS
Oscar Gabriel Reyes Pupo, Raúl M. Luque, Justo Castaño, Sebastián Ventura
2019 J jnl
Performing Multi-Target Regression via a Parameter Sharing-Based Deep Network.
Int. J. Neural Syst.
Oscar Gabriel Reyes Pupo, Sebastián Ventura
2018 — conf
A gene expression programming method for multi-target regression.
LOPAL
Oscar Gabriel Reyes Pupo, Jose María Moyano Murillo, José María Luna, Sebastián Ventura
2018 J jnl
A locally weighted learning method based on a data gravitation model for multi-target regression.
Int. J. Comput. Intell. Syst.
Oscar Gabriel Reyes Pupo, Alberto Cano, Habib M. Fardoun, Sebastián Ventura
2018 J jnl
An ensemble-based method for the selection of instances in the multi-target regression problem.
Integr. Comput. Aided Eng.
Oscar Gabriel Reyes Pupo, Habib M. Fardoun, Sebastián Ventura
2018 J jnl
Effective active learning strategy for multi-label learning.
Neurocomputing
Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura
2018 J jnl
Evolutionary Strategy to Perform Batch-Mode Active Learning on Multi-Label Data.
ACM Trans. Intell. Syst. Technol.
Oscar Gabriel Reyes Pupo, Sebastián Ventura
2018 J jnl
Statistical comparisons of active learning strategies over multiple datasets.
Knowl. Based Syst.
Oscar Gabriel Reyes Pupo, Abdulrahman H. Altalhi, Sebastián Ventura
2016 J jnl
Effective lazy learning algorithm based on a data gravitation model for multi-label learning.
Inf. Sci.
Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura
2016 J jnl
JCLAL: A Java Framework for Active Learning.
J. Mach. Learn. Res.
Oscar Gabriel Reyes Pupo, Eduardo Pérez, María del Carmen Rodríguez-Hernández, Habib M. Fardoun, Sebastián Ventura
2015 J jnl
Scalable extensions of the ReliefF algorithm for weighting and selecting features on the multi-label learning context.
Neurocomputing
Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura
2014 J jnl
Evolutionary feature weighting to improve the performance of multi-label lazy algorithms.
Integr. Comput. Aided Eng.
Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura
2013 — conf
ReliefF-ML: An Extension of ReliefF Algorithm to Multi-label Learning.
CIARP (2)
Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura Soto
2012 C conf
Learning similarity metric to improve the performance of lazy multi-label ranking algorithms.
ISDA
Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura