Antonio Jesús Rivera Rivas
Contact
arivera@uq@U@Q838qrjaen.es
Organization
UJA| Total | From 2019: | |
|---|---|---|
| Citas | Total: 2679 | From 2019: 1942 |
| Índice H | Total: 26 | From 2019: 21 |
| Índice i10 | Total: 40 | From 2019: 32 |
Papers (105)
| Title | Authors | Year |
|---|---|---|
| DESReg: Dynamic Ensemble Selection library for Regression tasks | MD Pérez-Godoy, M Molina, F Martínez, D Elizondo, F Charte, AJ Rivera. | 2024 |
| Transfer Learning with Foundational Models for Time Series Forecasting using Low-Rank Adaptations | M Germán-Morales, AJ Rivera-Rivas, MJ Díaz, CJ Carmona. | 2024 |
| Nets4Learning: A Web Platform for Designing and Testing ANN/DNN Models | A Mudarra, D Valdivia, P Ducange, M Germán, AJ Rivera, .... | 2024 |
| 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 |
| mldr. resampling: Efficient Reference Implementations of Multilabel Resampling Algorithms | AJ Rivera, MA Dávila, MJ del Jesus, D Elizondo, F Charte. | 2023 |
| Analysis of Transformer Model Applications | MI Cabrera-Bermejo, MJ Del Jesus, AJ Rivera, D Elizondo, F Charte, .... | 2023 |
| NOSpcimen: A First Approach to Unsupervised Discarding of Empty Photo Trap Images | D de la Rosa, A Álvarez, R Pérez, G Garrote, AJ Rivera, MJ del Jesus, .... | 2023 |
| PARDINUS: Weakly supervised discarding of photo-trapping empty images based on autoencoders | D de la Rosa, AJ Rivera, MJ del Jesus, 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 |
| 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 |
| 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 |
| 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 |
| AEkNN: An AutoEncoder kNN—Based Classifier With Built-in Dimensionality Reduction | FJ Pulgar, F Charte, AJ Rivera, MJ Del Jesus. | 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 |
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