Óscar Gabriel Reyes Pupo

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Sebastián Ventura (ORCID: 0000-000...Professor of Computing and Artificial Intelligence, University of CordobaDirección de correo verificada de uco.es
Carlos MorellProfessor of Computer Science, Universidad Central "Marta Abreu" de Las VillasDirección de correo verificada de uclv.edu.cu
Justo P. CastañoIMIBIC, Universidad de CordobaDirección de correo verificada de uco.es
Emilia Alors PérezMaimonides Institute of Biomedical Research of Cordoba (IMIBIC); Reina Sofia University Hospital (HURS); Department of Cell Biology, Physiology and Immunology, University of Cordoba (UCO); CIBER Physiopathology of Obesity and Nutrition (CIBERobn); Agrifood Campus of International Excellence (CeiA3), Cordoba, Spain.Dirección de correo verificada de uco.es
Eduardo Pérez PerdomoMaimónides Institute of Biomedical Research (IMIBIC), Córdoba - Spain.Dirección de correo verificada de imibic.org
Habib M. FardounKing Abdulaziz UniversityDirección de correo verificada de kau.edu.sa
José Lopez-MirandaProfesor de Medicina. Hospital Universitario Reina Sofía. IMIBIC. Universidad de Córdoba. CIBEROBNDirección de correo verificada de uco.es
Jose M. MoyanoPostdoctoral researcher at Dpt. of Computer Science and AI, University of GranadaDirección de correo verificada de uco.es
María del Carmen Rodríguez-Hernánd...Ph.D., University of ZaragozaDirección de correo verificada de unizar.es
Alberto CanoAssociate Professor of Computer Science, Virginia Commonwealth University, USADirección de correo verificada de vcu.edu
José María Luna (ORCID: 0000-0003-...Associate Professor of Computing and Artificial Intelligence, University of CordobaDirección de correo verificada de uco.es

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Óscar Gabriel Reyes Pupo

Data Scientist Leader in Healios AG

Dirección de correo verificada de healios.tech

Deep Learning Machine Learning Data mining Metaheuristics Algorithms and Data structures


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	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	163	2015
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	58	2019
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	57	2020
Effective active learning strategy for multi-label learning O Reyes, C Morell, S Ventura Neurocomputing 273, 494-508, 2018	50	2018
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	44	2021
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	42	2019
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	42	2014
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	41	2020
Statistical comparisons of active learning strategies over multiple datasets O Reyes, AH Altalhi, S Ventura Knowledge-Based Systems 145, 274-288, 2018	41	2018
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	36	2018
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	34	2013
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	33	2016
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	32	2018
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	26	2016
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	23	2018
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	16	2019
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	7	2021
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	7	2018
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	6	2020
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	6	2012

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