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Óscar Gabriel Reyes Pupo
Óscar Gabriel Reyes Pupo
Data Scientist Leader in Healios AG
Dirección de correo verificada de healios.tech
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Año
Scalable extensions of the ReliefF algorithm for weighting and selecting features on the multi-label learning context
O Reyes, C Morell, S Ventura
Neurocomputing 161, 168-182, 2015
1632015
Performing Multi-Target Regression via a Parameter Sharing-based Deep Network
O Reyes, S Ventura
International Journal of Neural Systems 29 (9 (1950014)), 1-22, 2019
582019
Dysregulation of the splicing machinery is directly associated to aggressiveness of prostate cancer
JM Jiménez-Vacas, V Herrero-Aguayo, AJ Montero-Hidalgo, ...
EBioMedicine 51, 102547, 2020
572020
Effective active learning strategy for multi-label learning
O Reyes, C Morell, S Ventura
Neurocomputing 273, 494-508, 2018
502018
Convolutional neural networks for the automatic diagnosis of melanoma: An extensive experimental study
E Perez, O Reyes, S Ventura
Medical image analysis 67, 101858, 2021
442021
Dysregulation of the splicing machinery is associated to the development of non-alcoholic fatty liver disease
M del Río-Moreno, E Alors-Pérez, S González-Rubio, G Ferrín, O Reyes, ...
The Journal of Clinical Endocrinology & Metabolism, jc.2019-00021, https …, 2019
422019
Evolutionary feature weighting to improve the performance of multi-label lazy algorithms
O Reyes, C Morell, S Ventura
Integrated Computer-Aided Engineering 21 (4), 339-354, 2014
422014
Splicing machinery dysregulation drives glioblastoma development/aggressiveness: oncogenic role of SRSF3
AC Fuentes-Fayos, MC Vázquez-Borrego, JM Jimenez-Vacas, L Bejarano, ...
Brain 143 (11), 3273-3293, 2020
412020
Statistical comparisons of active learning strategies over multiple datasets
O Reyes, AH Altalhi, S Ventura
Knowledge-Based Systems 145, 274-288, 2018
412018
Evolutionary Strategy to perform Batch-Mode Active Learning on Multi-Label Data
O Reyes, S Ventura
ACM Transactions on Intelligent Systems and Technology 9 (4), 46:1--46:26, 2018
362018
ReliefF-ML: an extension of ReliefF algorithm to multi-label learning
OGR Pupo, C Morell, SV Soto
Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2013
342013
JCLAL: A Java Framework for Active Learning
O Reyes, E Pérez, M del Carmen Rodrıguez-Hernández, HM Fardoun, ...
Journal of Machine Learning Research 17 (95), 1-5, 2016
332016
Changes in splicing machinery components influence, precede, and early predict the development of type 2 diabetes: from the CORDIOPREV study
MD Gahete, M del Rio-Moreno, A Camargo, JF Alcala-Diaz, E Alors-Perez, ...
EBioMedicine 37, 356-365, 2018
322018
Effective lazy learning algorithm based on a data gravitation model for multi-label learning
O Reyes, C Morell, S Ventura
Information Sciences 340, 159-174, 2016
262016
A locally weighted learning method based on a data gravitation model for multi-target regression
O Reyes, A Cano, HM Fardoun, S Ventura
International Journal of Computational Intelligence Systems 11, 282-295, 2018
232018
Signal Speech Reconstruction and Noise removal using Convolutional Denoising Audioencoders with Neural Deep Learning
A Houda, O Chakkor, O Reyes, S Ventura
Analog Integrated Circuits and Signal Processing. https://doi.org/10.1007 …, 2019
162019
Performing multi-target regression via gene expression programming-based ensemble models
J Moyano, O Reyes, S Fardoun, Habib M., Ventura
Neurocomputing 432 (7), 275-287, 2021
72021
An ensemble-based method for the selection of instances in the multi-target regression problem
O Reyes, H Fardoun, S Ventura
Integrated Computer-Aided Engineering 25 (4), 305-320, 2018
72018
A supervised machine learning-based methodology for analyzing dysregulation in splicing machinery: An application in cancer diagnosis
O Reyes, E Perez, RM Luque, J Castano, S Ventura
Artificial Intelligence in Medicine 108, 101950, 2020
62020
Learning similarity metric to improve the performance of lazy multi-label ranking algorithms
O Reyes, C Morell, S Ventura
2012 12th International Conference on Intelligent Systems Design and …, 2012
62012
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Artículos 1–20