XAIRE: An ensemble-based methodology for determining the relative importance of variables in regression tasks. Application to a hospital emergency department |
AJ Rivera, JC Muñoz, MD Pérez-Goody, BS de San Pedro, F Charte, .... |
2023 |
Time Series Forecasting by Generalized Regression Neural Networks Trained with Multiple Series |
F Martínez, MP Frías, MD Pírez-Godoy, AJ Rivera. |
2022 |
Analysis of clustering methods for crop type mapping using satellite imagery |
AJ Rivera, MD Pérez-Godoy, D Elizondo, L Deka, MJ del Jesus. |
2022 |
ClEnDAE: A classifier based on ensembles with built-in dimensionality reduction through denoising autoencoders |
FJ Pulgar, F Charte, AJ Rivera, MJ del Jesus. |
2021 |
ENGAGING PHARMACIES TO INCREASE ADHERENCE FOR MEDICARE MEMBERS |
A Rivera, J Gonzalez, L Lorenzo, K Ocasio, J Mateo. |
2021 |
Choosing the proper autoencoder for feature fusion based on data complexity and classifiers: Analysis, tips and guidelines |
FJ Pulgar, F Charte, AJ Rivera, MJ del Jesus. |
2020 |
EvoAAA: An evolutionary methodology for automated neural autoencoder architecture search |
F Charte, AJ Rivera, F Martínez, MJ del Jesus. |
2020 |
A Preliminary Study on Crop Classification with Unsupervised Algorithms for Time Series on Images with Olive Trees and Cereal Crops |
AJ Rivera, MD Pérez-Godoy, D Elizondo, L Deka, MJ del Jesus. |
2020 |
El ecosistema de aprendizaje del estudiante universitario en la post-pandemia. Metodologías y herramientas |
F Charte Ojeda, AJ Rivera Rivas, J Medina, M Espinilla Estevez. |
2020 |
A cohort of patients with COVID-19 in a major teaching hospital in Europe (preprint) |
AM Borobia, AJ Carcas, F Arnalich, R Alvarez-Sala, J Montserrat, .... |
2020 |
Dealing with difficult minority labels in imbalanced mutilabel data sets |
F Charte, AJ Rivera, MJ del Jesus, F Herrera. |
2019 |
REMEDIAL-HwR: Tackling multilabel imbalance through label decoupling and data resampling hybridization |
F Charte, AJ Rivera, MJ del Jesus, F Herrera. |
2019 |
Choosing the proper autoencoder for feature fusion based on data complexity and classifiers: Analysis, Tips and guidelines. |
FJ Pulgar, F Charte, AJ Rivera, MJ del Jesus. |
2019 |
A First Approximation to the Effects of Classical Time Series Preprocessing Methods on LSTM Accuracy |
DT Viedma, AJR Rivas, FC Ojeda, MJ del Jesus Díaz. |
2019 |
Automatic Time Series Forecasting with GRNN: A Comparison with Other Models |
F Martínez, F Charte, AJ Rivera, MP Frías. |
2019 |
Automating Autoencoder Architecture Configuration: An Evolutionary Approach |
F Charte, AJ Rivera, F Martínez, MJ del Jesus. |
2019 |
predtoolsTS: R package for streamlining time series forecasting |
F Charte, A Vico, MD Pérez-Godoy, AJ Rivera. |
2019 |
Time Series Forecasting with KNN in R: the tsfknn Package |
F Martínez, MP Frías, F Charte, AJ Rivera. |
2019 |
Time Series Forecasting with KNN in R: the tsfknn Package. |
F Martínez, MP Frías, F Charte, AJ Rivera. |
2019 |
Tips, guidelines and tools for managing multi-label datasets: The mldr. datasets R package and the Cometa data repository |
F Charte, AJ Rivera, D Charte, MJ del Jesus, F Herrera. |
2018 |
AEkNN: An AutoEncoder kNN-Based Classifier With Built-in Dimensionality Reduction |
FJ Pulgar, F Charte, AJ Rivera, MJ del Jesus. |
2018 |
Nuevas arquitecturas hardware de procesamiento de alto rendimiento para aprendizaje profundo |
AJ Rivera, F Charte, M Espinilla, MD Pérez-Godoy. |
2018 |
A First Approach to Face Dimensionality Reduction Through Denoising Autoencoders |
FJ Pulgar, F Charte, AJ Rivera, MJ del Jesus. |
2018 |
Una primera aproximacion a la prediccion de variables turısticas con Deep Learning |
D Trujillo, AJ Rivera, F Charte, MJ del Jesus. |
2018 |
Análisis del impacto de datos desbalanceados en el rendimiento predictivo de redes neuronales convolucionales |
FJ Pulgar, AJ Rivera, F Charte, MJ del Jesus. |
2018 |
Dealing with seasonality by narrowing the training set in time series forecasting with kNN |
F Martínez, MP Frías, MD Pérez-Godoy, AJ Rivera. |
2018 |
MEFASD-BD: multi-objective evolutionary fuzzy algorithm for subgroup discovery in big data environments-a MapReduce solution |
F Pulgar-Rubio, AJ Rivera-Rivas, MD Pérez-Godoy, P González, .... |
2017 |
On the impact of imbalanced data in convolutional neural networks performance |
FJ Pulgar, AJ Rivera, F Charte, MJ del Jesus. |
2017 |
Comparative analysis of data mining and response surface methodology predictive models for enzymatic hydrolysis of pretreated olive tree biomass |
F Charte, I Romero, MD Pérez-Godoy, AJ Rivera, E Castro. |
2017 |
Evolución tecnológica del hardware de vídeo y las GPU en los ordenadores personales |
FC Ojeda, AJ Rueda, M Espinilla, AJR Riva. |
2017 |
Uso de dispositivos FPGA como apoyo a la ensenanza de asignaturas de arquitectura de computadores |
FC Ojeda, M Espinilla, AJR Riva, FJP Rubio. |
2017 |
A Transformation Approach Towards Big Data Multilabel Decision Trees |
AJR Rivas, FC Ojeda, FJ Pulgar, MJ del Jesus. |
2017 |
A methodology for applying k-nearest neighbor to time series forecasting |
F Martínez, MP Frías, MD Pérez, AJ Rivera. |
2017 |
Modeling the Transformation of Olive Tree Biomass into Bioethanol with Reg-CO RBFN |
F Charte Ojeda, I Romero Pulido, AJ Rivera Rivas, E Castro Galiano. |
2017 |
Modeling the Transformation of Olive Tree Biomass into Bioethanol with Reg-CORBFN |
FC Ojeda, IR Pulido, AJR Rivas, EC Galiano. |
2017 |
Estimating the Maximum Power Delivered by Concentrating Photovoltaics Technology Through Atmospheric Conditions Using a Differential Evolution Approach |
CJ Carmona, F Pulgar, AJ Rivera-Rivas, MJ del Jesus, J Aguilera. |
2016 |
R ultimate multilabel dataset repository |
F Charte, D Charte, A Rivera, MJ del Jesus, F Herrera. |
2016 |
On the impact of dataset complexity and sampling strategy in multilabel classifiers performance |
F Charte, A Rivera, MJ del Jesus, F Herrera. |
2016 |
Recognition of activities in resource constrained environments; reducing the computational complexity |
M Espinilla, A Rivera, MD Pérez-Godoy, J Medina, L Martínez, C Nugent. |
2016 |
Ensemble-based classifiers |
F Herrera, F Charte, AJ Rivera, MJ del Jesus. |
2016 |
Gamificación en procesos de autoentrenamiento y autoevaluación. Experiencia en la asignatura de Arquitectura de Computadores |
M Espinilla, A Fernández, J Santamaría, AJ Rivera Rivas. |
2016 |
Explotación de la potencia de procesamiento mediante paralelismo: un recorrido histórico hasta la GPGPU |
F Charte Ojeda, AJR Riva, FJP Rubio, MJ del Jesús Díaz. |
2016 |
Case Studies and Metrics |
F Herrera, F Charte, AJ Rivera, MJ del Jesus. |
2016 |
Transformation-Based Classifiers |
F Herrera, F Charte, AJ Rivera, MJ del Jesus. |
2016 |
Dimensionality Reduction |
F Herrera, F Charte, AJ Rivera, MJ del Jesus. |
2016 |
Multilabel Software |
F Herrera, F Charte, AJ Rivera, MJ del Jesus. |
2016 |
Imbalance in Multilabel Datasets |
F Herrera, F Charte, AJ Rivera, MJ del Jesus. |
2016 |
Adaptation-Based Classifiers |
F Herrera, F Charte, AJ Rivera, MJ del Jesus. |
2016 |
Multilabel classification |
F Herrera, F Charte, AJ Rivera, MJ Del Jesus. |
2016 |
Multilabel Classification: Problem Analysis, Metrics and Techniques |
F Herrera, F Charte, AJ Rivera, MJ del Jesus. |
2016 |
A differential evolution proposal for estimating the maximum power delivered by CPV modules under real outdoor conditions |
B García-Domingo, CJ Carmona, AJ Rivera-Rivas, MJ del Jesús, .... |
2015 |
Una primera aproximación al descubrimiento de subgrupos bajo el paradigma MapReduce |
F Pulgar-Rubio, CJ Carmona, AJ Rivera-Rivas, P González, MJ del Jesus. |
2015 |
Addressing imbalance in multilabel classification: Measures and random resampling algorithms |
F Charte, AJ Rivera, MJ del Jesus, F Herrera. |
2015 |
MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation |
F Charte, AJ Rivera, MJ del Jesus, F Herrera. |
2015 |
QUINTA: a question tagging assistant to improve the answering ratio in electronic forums |
F Charte, AJ Rivera, MJ del Jesus, F Herrera. |
2015 |
Resampling multilabel datasets by decoupling highly imbalanced labels |
F Charte, A Rivera, MJ del Jesus, F Herrera. |
2015 |
CORBFN-CS: First Approach Introducing Cost-Sensitivity in the Cooperative-Competitive RBFN Design |
MD Pérez-Godoy, AJ Rivera, F Charte, MJ del Jesus. |
2015 |
GenRBFNSpark: A first implementation in Spark of a genetic algorithm to RBFN design |
AJ Rivera, MD Pérez-Godoy, F Pulgar, MJ del Jesus. |
2015 |
CO RBFN-CS: First Approach Introducing Cost-Sensitivity in the Cooperative-Competitive RBFN Design |
MD Pérez-Godoy, AJ Rivera, F Charte, MJ del Jesus. |
2015 |
CO RBFN-CS: First Approach Introducing Cost-Sensitivity in the Cooperative-Competitive RBFN Design |
MD Pérez-Godoy, AJ Rivera, F Charte, MJ del Jesus. |
2015 |
Training algorithms for radial basis function networks to tackle learning processes with imbalanced data-sets |
MD Pérez-Godoy, AJ Rivera, CJ Carmona, MJ del Jesús. |
2014 |
Concurrence among imbalanced labels and its influence on multilabel resampling algorithms |
F Charte, A Rivera, MJ del Jesus, F Herrera. |
2014 |
LI-MLC: A Label Inference Methodology for Addressing High Dimensionality in the Label Space for Multilabel Classification |
F Charte, AJ Rivera, MJ Del Jesus, F Herrera. |
2014 |
MLeNN: a first approach to heuristic multilabel undersampling |
F Charte, AJ Rivera, MJ del Jesus, F Herrera. |
2014 |
Propuesta de una asignatura de Diseño de Servidores para la especialidad de Tecnologías de Información |
AJ Rivera Rivas, M Espinilla, A Fernández Hilario, J Santamaría López, .... |
2014 |
A first approach to deal with imbalance in multi-label datasets |
F Charte, A Rivera, MJ del Jesus, F Herrera. |
2013 |
Characterization of concentrating photovoltaic modules by cooperative competitive radial basis function networks |
AJ Rivera, B García-Domingo, MJ Del Jesus, J Aguilera. |
2013 |
A Performance Study of Concentrating Photovoltaic Modules Using Neural Networks: An Application with CO2RBFN |
AJ Rivera, B García-Domingo, MJ del Jesus, J Aguilera. |
2013 |
A first analysis of the effect of local and global optimization weights methods in the cooperative-competitive design of RBFN for imbalanced environments |
MD Pérez-Godoy, AJ Rivera, MJ Del Jesus, F Martínez. |
2013 |
Use of protrombin complex concentrates for urgent reversal of dabigatran in the emergency department: a pilot study |
M Quintana, AM Borobia, A Martinez Virto, S Fabra, A Rivera, .... |
2013 |
Improving multi-label classifiers via label reduction with association rules |
F Charte, A Rivera, MJ del Jesus, F Herrera. |
2012 |
Multi-label Testing for CO2RBFN: A First Approach to the Problem Transformation Methodology for Multi-label Classification |
AJ Rivera, F Charte, MD Pérez-Godoy, MJ del Jesus. |
2011 |
A study on the medium-term forecasting using exogenous variable selection of the extra-virgin olive oil with soft computing methods |
AJ Rivera, P Pérez-Recuerda, MD Pérez-Godoy, MJ Del Jesús, MP Frías, .... |
2011 |
A summary on the study of the medium-term forecasting of the extra-virgen olive oil price |
AJ Rivera, MD Pérez-Godoy, MJ Del Jesus, P Pérez-Recuerda, MP Frías, .... |
2011 |
CO2RBFN for Short and Medium Term Forecasting of the Extra-Virgin Olive Oil Price |
MD Pérez-Godoy, P Pérez-Recuerda, MP Frías, AJ Rivera, CJ Carmona, .... |
2010 |
CO 2RBFN for short-term forecasting of the extra virgin olive oil price in the Spanish market |
MD Pérez-Godoy, P Pérez, AJ Rivera, MJ del Jesús, CJ Carmona, .... |
2010 |
A preliminary study on mutation operators in cooperative competitive algorithms for RBFN design |
MD Pérez-Godoy, AJ Rivera, CJ Carmona, MJ del Jesus. |
2010 |
Potenciando el aprendizaje proactivo con ILIAS&WebQuest: aprendiendo a paralelizar algoritmos con GPUs |
J Santamaría, M Espinilla, AJ Rivera, S Romero. |
2010 |
GP-COACH: Genetic Programming-based learning of COmpact and ACcurate fuzzy rule-based classification systems for High-dimensional problems |
FJ Berlanga, AJ Rivera, MJ del Jesús, F Herrera. |
2010 |
Analysis of an evolutionary RBFN design algorithm, CO2RBFN, for imbalanced data sets |
MD Pérez-Godoy, A Fernández, AJ Rivera, MJ del Jesus. |
2010 |
CO2RBFN: an evolutionary cooperative–competitive RBFN design algorithm for classification problems |
MD Perez-Godoy, AJ Rivera, FJ Berlanga, MJ Del Jesus. |
2010 |
Co2rbfn: predicción de series temporales con un enfoque cooperativo-̃́ competitivo |
M Pérez-Godoy, P Pérez, A Rivera, M Del Jesus, PL López. |
2010 |
Intelligent systems in long-term forecasting of the extra-virgin olive oil price in the Spanish market |
MD Pérez-Godoy, P Pérez, AJ Rivera, MJ del Jesús, MP Frías, M Parras. |
2010 |
Applying multiobjective RBFNNs optimization and feature selection to a mineral reduction problem |
A Guillén, G Rubio, I Toda, A Rivera, H Pomares, I Rojas. |
2010 |
Mejoras en el diseño multiobjetivo de redes de funciones de base radial |
PL López, AJ Rivera, CJ Carmona, MD Pérez-Godoy. |
2010 |
CO 2 RBFN: an evolutionary cooperative–competitive RBFN design algorithm for classification problems |
MD Perez-Godoy, AJ Rivera, FJ Berlanga, MJ Del Jesus. |
2010 |
CO2RBFN for Short and Medium Term Forecasting of the Extra-Virgin Olive Oil Price. |
MD Pérez-Godoy, P Pérez-Recuerda, MP Frías, AJR Rivas, CJ Carmona, .... |
2010 |
EMORBFN: An Evolutionary Multiobjetive Optimization Algorithm for RBFN Design |
PL López, AJ Rivera, MD Pérez-Godoy, MJ del Jesus, C Carmona. |
2009 |
A Preliminar Analysis of CO2RBFN in Imbalanced Problems |
MD Pérez-Godoy, AJ Rivera, A Fernández, MJ del Jesús, F Herrera. |
2009 |
Adaptación de una asignatura avanzada de redes de computadores al modelo de docencia virtual dentro del marco del Espacio Europeo de Educación Superior |
AJ Rivera, CJ Carmona, MD Pérez-Godoy, MJ del Jesus. |
2009 |
A preliminary study of the effect of feature selection in evolutionary RBFN design |
MD Perez-Godoy, JJ Aguilera, FJ Berlanga, VM Rivas, AJ Rivera. |
2008 |
An study on data mining methods for short-term forecasting of the extra virgin olive oil price in the Spanish market |
P Pérez, MP Frías, MD Pérez-Godoy, AJ Rivera, MJ del Jesús, M Parras, .... |
2008 |
A new hybrid methodology for cooperative-coevolutionary optimization of radial basis function networks |
AJ Rivera, I Rojas, J Ortega, MJ del Jesús. |
2007 |
CoEvRBFN: an approach to solving the classification problem with a hybrid cooperative-coevolutive algorithm |
MD Pérez-Godoy, AJ Rivera, MJ Del Jesus, I Rojas. |
2007 |
Optimización de CoEvRBF para aumentar su eficiencia en tareas de clasificación |
MD PérezYGodoy, AJ Rivera, MJJI Rojas. |
2007 |
Application of ANOVA to a cooperative-coevolutionary optimization of RBFNs |
AJ Rivera, I Rojas, J Ortega. |
2005 |
La orientación escolar en centros educativos |
M Pérez, A Rivera. |
2005 |
Co-evolutionary algorithm for RBF by self-organizing population of neurons |
AJ Rivera, J Ortega, I Rojas, MJ del Jesús. |
2003 |
Diseño y optimización de redes de funciones de base radial mediante técnicas bioinspiradas |
AJ Rivera Rivas. |
2003 |
Aproximación de funciones con evolución difusa mediante cooperación y competición de RBFs |
A Rivera, J Ortega, MJ del Jesus, J González. |
2002 |
Optimizing RBF networks with cooperative/competitive evolution of units and fuzzy rules |
AJ Rivera, J Ortega, I Rojas, A Prieto. |
2001 |
Design of RBF networks by cooperative/competitive evolution of units |
AJ Rivera, J Ortega, A Prieto. |
2001 |
Learning and Other Plasticity Phenomena, and Complex Systems Dynamics-Optimizing RBF Networks with Cooperative/Competitive Evolution of Units and Fuzzy Rules |
AJ Rivera, J Ortega, I Rojas, A Prieto. |
2001 |
La asignatura de Planificación de Sistemas Informáticos en Ingeniería Técnica en Informática de Gestión |
P González, MD Pérez, AJ Rivera. |
1999 |
Prácticas para una asignatura de Fundamentos de Informática |
P González, J Ruiz de Miras, MD Pérez, AJ Rivera. |
1998 |
Lupus miliaris disseminatus faciei–an unusual granuloma of the face |
M Pérez, A Rivera, JL Sánchez. |
1984 |