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Book

El pasado de la computación personal. Historia de la microinformática (2a Edición), Charte, Francisco, and García Lina , (2019)

Multilabel Classification: Problem Analysis, Metrics and Techniques, Herrera, F., Charte Francisco, Rivera Antonio J., and del Jesus M. J. , (2016)

Conference Paper

A First Approach to Deal with Imbalance in Multi-label Datasets, Charte, Francisco, Rivera Antonio J., del Jesus M. J., and Herrera F. , 8th International Conference on Hybrid Artificial Intelligent Systems (HAIS 2013), 9, Salamanca (Spain), p.150-160, (2013)

2013-HAIS-ImbalanceMultilabel.pdf (194.4 KB)

A First Approach to Face Dimensionality Reduction Through Denoising Autoencoders, Pulgar-Rubio, F., Charte Francisco, Rivera Antonio J., and del Jesus M. J. , 19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018, 11, Madrid (Spain), p.439–447, (2018)

2018-IDEAL-DimensionalityDAE.pdf (2.45 MB)

A first approach towards a fuzzy decision tree for multilabel classification, Prati, Ronaldo C., Charte Francisco, and Herrera F. , 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 7, Naples (Italy), p.1–6, (2017)

2017-IEEE-FuzzyDTMLC.pdf (299.08 KB)

A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines, Charte, David, Charte Francisco, García S., del Jesus M. J., and Herrera F. , XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018), 10, Granada (Spain), p.949–950, (2018)

2018-CAEPIA-TutorialAEs.pdf (59.39 KB)

A specialized lazy learner for time series forecasting, Martínez, Francisco, Frías M.P., Charte Francisco, and Rivera Antonio J. , 17th International Conference on Computational and Mathematical Methods in Science and Engineering, CMMSE 2017, 7, Costa Ballena, Rota, Cáadiz (Spain), p.1397–1403, (2017)

2017-CMMSE-SpecializedLazyLearner.pdf (211.11 KB)

A Transformation Approach Towards Big Data Multilabel Decision Trees, Rivera, Antonio J., Charte Francisco, Pulgar-Rubio F., and del Jesus M. J. , 14th International Work-Conference on Artificial Neural Networks (IWANN 2017), 6, Cádiz (Spain), p.73–84, (2017)

2017-IWANN-BigDataMLDT.pdf (372.37 KB)

Alternative OVA Proposals for Cooperative Competitive RBFN Design in Classification Tasks, Charte, Francisco, Rivera Antonio J., Pérez-Godoy M.D., and del Jesus M. J. , 12th International Work-Conference on Artificial Neural Networks (IWANN 2013), Tenerife (Spain), p.331-338, (2013)

2013-IWANN-AlternativeOVA.pdf (146.42 KB)

An Approximation to Deep Learning Touristic-Related Time Series Forecasting, Trujillo, Daniel, Rivera Antonio J., Charte Francisco, and del Jesus M. J. , 19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018, 11, Madrid (Spain), p.448–456, (2018)

2018-IDEAL-LSTMTouristic.pdf (2.13 MB)

An ensemble strategy for forecasting the extra-virgin olive oil price in Spain, Rivera, Antonio J., Pérez-Godoy M.D., Charte Francisco, Pulgar-Rubio F., and del Jesus M. J. , International work-conference on Time Series, ITISE 2015, 7, Granada (Spain), p.506–516, (2015)

2015-ITISE-ForecastOliveOil.pdf (547.65 KB)

Análisis del impacto de datos desbalanceados en el rendimiento predictivo de redes neuronales convolucionales, Pulgar-Rubio, F., Rivera Antonio J., Charte Francisco, and Díaz María J. del Jesu , XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018), 10, Granada (Spain), p.1213–1218, (2018)

2018-CAEPIA-DesbalanceoCNNs.pdf (228.43 KB)

Análisis visual de técnicas no supervisadas de deep learning con el paquete dlvisR, Charte, David, Charte Francisco, and Herrera F. , XVII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2016), 9, Salamanca (Spain), p.895–904, (2016)

2016-CAEPIA-dlvisR.pdf (2.56 MB)

CO2RBFN-CS: First Approach Introducing Cost-Sensitivity in the Cooperative-Competitive RBFN Design, Pérez-Godoy, M.D., Rivera Antonio J., Charte Francisco, and del Jesus M. J. , 13th International Work-Conference on Artificial Neural Networks (IWANN 2015), 6, Palma de Mallorca (Spain), p.361–373, (2015)

2015-IWANN-CostSensitiveCO2RBFN.pdf (360.2 KB)

Combining simple exponential smoothing models for time series forecasting, Martínez, Francisco, Pérez-Godoy M.D., Charte Francisco, and del Jesus M. J. , International work-conference on Time Series, ITISE 2016, 6, Granada (Spain), p.635-644, (2016)

2016-ITISE-ExponentialSmoothing.pdf (1.13 MB)

Concurrence among Imbalanced Labels and Its Influence on Multilabel Resampling Algorithms, Charte, Francisco, Rivera Antonio J., del Jesus M. J., and Herrera F. , 9th International Conference on Hybrid Artificial Intelligent Systems (HAIS 2014), 6, Salamanca (Spain), p.110–121, (2014)

2014-HAIS-ConcurrenceLabels.pdf (1.12 MB)

Improving Multi-label Classifiers via Label Reduction with Association Rules, Charte, Francisco, Rivera Antonio J., del Jesus M. J., and Herrera F. , 7th International Conference on Hybrid Artificial Intelligent Systems (HAIS 2012), 9, Salamanca (Spain), p.188–199, (2012)

2012-HAIS-LabelReduction.pdf (171.47 KB)

mldr: Paquete R para Exploración de Datos Multietiqueta, Charte, David, and Charte Francisco , XVI Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2015), 11, Albacete (Spain), p.695–704, (2015)

2015-CAEPIA-mldr.pdf (2.39 MB)

MLeNN: A First Approach to Heuristic Multilabel Undersampling, Charte, Francisco, Rivera Antonio J., del Jesus M. J., and Herrera F. , 15th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2014, 9, Salamanca (Spain), p.1-9, (2014)

2014-IDEAL-MLeNN.pdf (184.04 KB)

MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation, Charte, Francisco, Rivera Antonio J., del Jesus M. J., and Herrera F. , XVII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2016), 9, Salamanca (Spain), p.821–822, (2016)

2016-CAEPIA-MLSMOTE.pdf (579.04 KB)

Modeling the Transformation of Olive Tree Biomass into Bioethanol with Reg-CO2RBFN, Charte, Francisco, Romero Inmaculada, Rivera Antonio J., and Castro Eulogio , 14th International Work-Conference on Artificial Neural Networks (IWANN 2017), 6, Cádiz (Spain), p.733–744, (2017)

2017IWANN-Biomass.pdf (158.82 KB)

Multi-label Testing for CO2RBFN: A First Approach to the Problem Transformation Methodology for Multi-label Classification, Rivera, Antonio J., Charte Francisco, Pérez-Godoy M.D., and del Jesus M. J. , 11th International Work-Conference on Artificial Neural Networks, IWANN 2011, 6, Torremolinos-Málaga (Spain), p.41–48, (2011)

2011-IWANN-MultilabelTestingCO2RBFN.pdf (131.76 KB)

On the Impact of Dataset Complexity and Sampling Strategy in Multilabel Classifiers Performance, Charte, Francisco, Rivera Antonio J., del Jesus M. J., and Herrera F. , 11th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2016, 4, Seville (Spain), p.500–511, (2016)

2016-HAIS-Complexity.pdf (1.28 MB)

On the Impact of Imbalanced Data in Convolutional Neural Networks Performance, Pulgar-Rubio, F., Rivera Antonio J., Charte Francisco, and del Jesus M. J. , 12th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2017, 6, La Rioja (Spain), p.220–232, (2017)

2017-HAIS-CNNImbalance-compressed.pdf (1.62 MB)

{QUINTA: A question tagging assistant to improve the answering ratio in electronic forums}, Charte, Francisco, Rivera Antonio J., del Jesus M. J., and Herrera F. , IEEE International Conference on Computer as a Tool, EUROCON 2015, 9, Salamanca (Spain), p.1-6, (2015)

2015-EUROCON-QUINTA.pdf (2.03 MB)

R Ultimate Multilabel Dataset Repository, Charte, Francisco, Charte David, Rivera Antonio J., del Jesus M. J., and Herrera F. , 11th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2016, 4, Seville (Spain), p.487–499, (2016)

2016-HAIS-RUMDR.pdf (1.3 MB)

Resampling Multilabel Datasets by Decoupling Highly Imbalanced Labels, Charte, Francisco, Rivera Antonio J., del Jesus M. J., and Herrera F. , 10th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2015, 6, Bilbao (Spain), p.489–501, (2015)

2015-HAIS-REMEDIAL.pdf (1.04 MB)

ReturnOK: El pasado de la computación personal, García, Lina, Ruano Ildefonso, Charte Francisco, Molina Andrés, and Balsas José R. , V Congreso Internacional de Patrimonio e Historia de la Ingeniería, 4, Las Palmas de Gran Canaria (Spain), p.1–19, (2010)

2010-CIPHI-Actas.pdf (1.16 MB)

Una primera aproximación a la predicción de variables turísticas con Deep Learning, Viedma, Daniel Trujillo, Rivera Antonio J., Charte Francisco, and Díaz María J. del Jesu , XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018), 10, Granada (Spain), p.939–943, (2018)

2018-CAEPIA-TurismoLSTMs.pdf (127.66 KB)

Usando Algoritmos de Descubrimiento de Subgrupos en R: El Paquete SDR, García-Vico, A.M., Charte Francisco, González P., Carmona C. J., and del Jesus M. J. , VII Simposio de Teoría y Aplicaciones de Minería de Datos, p.739-748, (2015)

2015 - TAMIDA-b.pdf (335 KB)

Journal Article

A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations, Charte, David, Charte Francisco, García S., and Herrera F. , Progress in Artificial Intelligence, Nov, (2018)

2018-PRAI-NonStandard-Accepted.pdf (951.61 KB)

Addressing imbalance in multilabel classification: Measures and random resampling algorithms, Charte, Francisco, Rivera Antonio J., del Jesus M. J., and Herrera F. , Neurocomputing, Volume 163, p.3–16, (2015)

2015-Neucom-AddressingImbalance.pdf (546.81 KB)

AEkNN: An AutoEncoder kNN-Based Classifier With Built-in Dimensionality Reduction, Pulgar-Rubio, F., Charte Francisco, Rivera Antonio J., and del Jesus M. J. , International Journal of Computational Intelligence Systems, 11/2018, Volume 12, p.436-452, (2018)

125905686.pdf (3.86 MB)

Comparative analysis of data mining and response surface methodology predictive models for enzymatic hydrolysis of pretreated olive tree biomass, Charte, Francisco, Romero Inmaculada, Pérez-Godoy M.D., Rivera Antonio J., and Castro Eulogio , Computers & Chemical Engineering, Volume 101, p.23–30, (2017)

2017-CACE-Biomasa.pdf (1.28 MB)

Dealing with difficult minority labels in imbalanced mutilabel data sets, Charte, Francisco, Rivera Antonio J., del Jesus M. J., and Herrera F. , Neurocomputing, Volume 326, p.39–53, (2019)

2019-NeucomDealingDifficultLabels.pdf (4.77 MB)

Evolución tecnológica del hardware de vídeo y las GPU en los ordenadores personales, Charte, Francisco, Rueda Antonio J., Espinilla Macarena, and Rivera Antonio J. , Enseñanza y aprendizaje de ingeniería de computadores. Revista de experiencias docentes en ingeniería de computadores, Volume 7, p.111–128, (2017)

2017-EAIC17-EvolucionGPUs.pdf (2.1 MB)

Explotación de la potencia de procesamiento mediante paralelismo: un recorrido histórico hasta la GPGPU, Charte, Francisco, Rivera Antonio J., Pulgar-Rubio F., and Díaz María J. del Jesu , Enseñanza y aprendizaje de ingeniería de computadores. Revista de experiencias docentes en ingeniería de computadores, Volume 6, p.19–33, (2016)

2016-EAIC16-Paralelismo.pdf (1.16 MB)

Is the average photon energy a unique characteristic of the spectral distribution of global irradiance?, Nofuentes, G, Gueymard CA, Aguilera J., Pérez-Godoy M.D., and Charte Francisco , Solar Energy, Volume 149, p.32–43, (2017)

2017-SolarEnergy-Photon-compressed.pdf (534.33 KB)

LI-MLC: A Label Inference Methodology for Addressing High Dimensionality in the Label Space for Multilabel Classification, Charte, Francisco, Rivera Antonio J., del Jesus M. J., and Herrera F. , IEEE Transactions on Neural Networks and Learning Systems, Volume 25, Number 10, p.1842-1854, (2014)

2014-TNNLS-LI-MLC.pdf (1.85 MB)

MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation, Charte, Francisco, Rivera Antonio J., del Jesus M. J., and Herrera F. , Knowledge-Based Systems, Volume 89, p.385–397, (2015)

2015-KBS-MLSMOTE.pdf (1.56 MB)

Nuevas arquitecturas hardware de procesamiento de alto rendimiento para aprendizaje profundo, Rivera, Antonio J., Charte Francisco, Espinilla Macarena, and Pérez-Godoy M.D. , Enseñanza y aprendizaje de ingeniería de computadores. Revista de experiencias docentes en ingeniería de computadores, Volume 8, p.67–83, (2018)

2018-EAIC18-HardwareAltoRend-compressed.pdf (431.68 KB)

Propuesta de una asignatura de Diseño de Servidores para la especialidad de Tecnologías de Información, Rivera, Antonio J., Espinilla Macarena, Fernández A., López José Santamarí, and Charte Francisco , Enseñanza y aprendizaje de ingeniería de computadores. Revista de experiencias docentes en ingeniería de computadores, Volume 4, p.15–24, (2014)

2014-EAIC14-AsignaturaDisenoServ.pdf (864.57 KB)

REMEDIAL-HwR: Tackling multilabel imbalance through label decoupling and data resampling hybridization, Charte, Francisco, Rivera Antonio J., del Jesus M. J., and Herrera F. , Neurocomputing, Volume 326, p.110–122, (2019)

2019-NeucomRemedial-HwR.pdf (2.83 MB)

ReturnOK, la Wiki sobre retroinformática, Cabrera, Lina García, Ruano Ildefonso, Charte Francisco, Aguilar Andrés Molina, and Almagro José Ramón Bal , Iniciación a la Investigación, Volume 5, p.1-5, (2010)

2010-IniciaInvUJA-ReturnOK.pdf (82.73 KB)

Ruta: implementations of neural autoencoders in R, Charte, David, Herrera F., and Charte Francisco , Knowledge-Based Systems, Volume 174, p.4-8, (2019)

Subgroup Discovery with Evolutionary Fuzzy Systems in R: the SDEFSR Package, García-Vico, A.M., Charte Francisco, González P., Carmona C. J., and del Jesus M. J. , The R Journal, Volume 8, Issue 2, p.307-323, (2016)

2016-Garcia-RJournal.pdf (2.56 MB)

Tips, guidelines and tools for managing multi-label datasets: The mldr.datasets R package and the Cometa data repository, Charte, Francisco, Rivera Antonio J., Charte David, del Jesus M. J., and Herrera F. , Neurocomputing, Volume 289, p.68–85, (2018)

2018-Neucom-TipsMLCCometa-compressed.pdf (1017.86 KB)

Uso de dispositivos FPGA como apoyo a la enseñanza de asignaturas de arquitectura de computadores, Charte, Francisco, Espinilla Macarena, Rivera Antonio J., and Pulgar-Rubio F. , Enseñanza y aprendizaje de ingeniería de computadores. Revista de experiencias docentes en ingeniería de computadores, Volume 7, p.37–52, (2017)

2017-EAIC17-FPGAsEnsenanza.pdf (1.48 MB)

Working with Multilabel Datasets in R: The mldr Package, Charte, Francisco, and Charte David , The R Journal, Volume 7, Number 2, p.149–162, (2015)

2015-RJournal-mldr.pdf (1.16 MB)