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Oscar Gabriel Reyes Pupo
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2020 – today
- 2023
- [j15]Eduardo Pérez, Oscar Gabriel Reyes Pupo:
Performing Melanoma Diagnosis by an Effective Multi-view Convolutional Network Architecture. Int. J. Comput. Vis. 131(11): 3094-3117 (2023) - [j14]Oscar Gabriel Reyes Pupo, Eduardo Pérez:
Performing Cancer Diagnosis via an Isoform Expression Ranking-based LSTM Model. ACM Trans. Intell. Syst. Technol. 14(6): 110:1-110:21 (2023) - 2021
- [j13]Jose M. Moyano, Oscar Gabriel Reyes Pupo, Habib M. Fardoun, Sebastián Ventura:
Performing multi-target regression via gene expression programming-based ensemble models. Neurocomputing 432: 275-287 (2021) - [j12]Eduardo Pérez, Oscar Gabriel Reyes Pupo, Sebastián Ventura:
Convolutional neural networks for the automatic diagnosis of melanoma: An extensive experimental study. Medical Image Anal. 67: 101858 (2021) - 2020
- [j11]Oscar Gabriel Reyes Pupo, Eduardo Pérez, Raúl M. Luque, Justo Castaño, Sebastián Ventura:
A supervised machine learning-based methodology for analyzing dysregulation in splicing machinery: An application in cancer diagnosis. Artif. Intell. Medicine 108: 101950 (2020)
2010 – 2019
- 2019
- [j10]Oscar Gabriel Reyes Pupo, Sebastián Ventura:
Performing Multi-Target Regression via a Parameter Sharing-Based Deep Network. Int. J. Neural Syst. 29(9): 1950014:1-1950014:22 (2019) - [c4]Oscar Gabriel Reyes Pupo, Raúl M. Luque, Justo Castaño, Sebastián Ventura:
A Supervised Methodology for Analyzing Dysregulation in Splicing Machinery: An Application in Cancer Diagnosis. CBMS 2019: 120-125 - 2018
- [j9]Oscar Gabriel Reyes Pupo, Habib M. Fardoun, Sebastián Ventura:
An ensemble-based method for the selection of instances in the multi-target regression problem. Integr. Comput. Aided Eng. 25(4): 305-320 (2018) - [j8]Oscar Gabriel Reyes Pupo, Alberto Cano, Habib M. Fardoun, Sebastián Ventura:
A locally weighted learning method based on a data gravitation model for multi-target regression. Int. J. Comput. Intell. Syst. 11(1): 282-295 (2018) - [j7]Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura:
Effective active learning strategy for multi-label learning. Neurocomputing 273: 494-508 (2018) - [j6]Oscar Gabriel Reyes Pupo, Abdulrahman H. Altalhi, Sebastián Ventura:
Statistical comparisons of active learning strategies over multiple datasets. Knowl. Based Syst. 145: 274-288 (2018) - [j5]Oscar Gabriel Reyes Pupo, Sebastián Ventura:
Evolutionary Strategy to Perform Batch-Mode Active Learning on Multi-Label Data. ACM Trans. Intell. Syst. Technol. 9(4): 46:1-46:26 (2018) - [c3]Oscar Gabriel Reyes Pupo, Jose María Moyano Murillo, José María Luna, Sebastián Ventura:
A gene expression programming method for multi-target regression. LOPAL 2018: 2:1-2:6 - 2016
- [j4]Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura:
Effective lazy learning algorithm based on a data gravitation model for multi-label learning. Inf. Sci. 340-341: 159-174 (2016) - [j3]Oscar Gabriel Reyes Pupo, Eduardo Pérez, María del Carmen Rodríguez-Hernández, Habib M. Fardoun, Sebastián Ventura:
JCLAL: A Java Framework for Active Learning. J. Mach. Learn. Res. 17: 95:1-95:5 (2016) - 2015
- [j2]Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura:
Scalable extensions of the ReliefF algorithm for weighting and selecting features on the multi-label learning context. Neurocomputing 161: 168-182 (2015) - 2014
- [j1]Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura:
Evolutionary feature weighting to improve the performance of multi-label lazy algorithms. Integr. Comput. Aided Eng. 21(4): 339-354 (2014) - 2013
- [c2]Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura Soto:
ReliefF-ML: An Extension of ReliefF Algorithm to Multi-label Learning. CIARP (2) 2013: 528-535 - 2012
- [c1]Oscar Gabriel Reyes Pupo, Carlos Morell, Sebastián Ventura:
Learning similarity metric to improve the performance of lazy multi-label ranking algorithms. ISDA 2012: 246-251
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