Francisco Charte

62 papers B 1C 1Misc 8Journal 41Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A didactic overview of Transformer applications: model variations and user guidelines. Log. J. IGPL Mi Cabrera-Bermejo, M. Germán, David de la Rosa, Mj Del Jesus, Aj Rivera, David A. Elizondo, Francisco Charte, M. Dolores Pérez-Godoy
2025	J	`jnl`	Addressing Multilabel Imbalance with an Efficiency-Focused Approach Using Diffusion Model-Generated Synthetic Samples. CoRR Francisco Charte, Miguel A. Dávila, María Dolores Pérez-Godoy, María José del Jesus
2025	—	`conf`	MORENA: Empty Images Detection Based on Unsupervised Reconstruction Error Analysis. IWANN (1) David de la Rosa, María José del Jesus, María Dolores Pérez-Godoy, Francisco Charte
2024	J	`jnl`	DESReg: Dynamic Ensemble Selection library for Regression tasks. Neurocomputing María Dolores Pérez-Godoy, Marta Molina, Francisco Martínez, David A. Elizondo, Francisco Charte, Antonio J. Rivera
2023	Misc	`conf`	Analysis of Transformer Model Applications. HAIS Maria Isabel Cabrera-Bermejo, María José del Jesus, Antonio J. Rivera, David A. Elizondo, Francisco Charte, M. Dolores Pérez-Godoy
2023	J	`jnl`	EvoAAA: An evolutionary methodology for automated \neural autoencoder architecture search. CoRR Francisco Charte, Antonio J. Rivera, Francisco Martínez, María José del Jesus
2023	—	`conf`	NOSpcimen: A First Approach to Unsupervised Discarding of Empty Photo Trap Images. IWANN (2) David de la Rosa, Antonio Álvarez, Ramón Pérez, Germán Garrote, Antonio J. Rivera, María José del Jesus, Francisco Charte
2023	J	`jnl`	PARDINUS: Weakly supervised discarding of photo-trapping empty images based on autoencoders. CoRR David de la Rosa, Antonio J. Rivera, María José del Jesus, Francisco Charte
2023	J	`jnl`	XAIRE: An ensemble-based methodology for determining the relative importance of variables in regression tasks. Application to a hospital emergency department. Artif. Intell. Medicine Antonio Jesús Rivera, J. Cobo Muñoz, M. Dolores Pérez-Godoy, B. Sáenz de San Pedro, Francisco Charte, David A. Elizondo, C. Rodríguez, M. L. Abolafia, A. Perea, María José del Jesus
2023	J	`jnl`	mldr.resampling: Efficient Reference Implementations of Multilabel Resampling Algorithms. CoRR Antonio J. Rivera, Miguel A. Dávila, David A. Elizondo, María José del Jesus, Francisco Charte
2023	J	`jnl`	mldr.resampling: Efficient reference implementations of multilabel resampling algorithms. Neurocomputing Antonio J. Rivera, Miguel A. Dávila, David A. Elizondo, María José del Jesus, Francisco Charte
2022	J	`jnl`	Reducing Data Complexity Using Autoencoders With Class-Informed Loss Functions. IEEE Trans. Pattern Anal. Mach. Intell. David Charte, Francisco Charte, Francisco Herrera
2022	J	`jnl`	Strategies for time series forecasting with generalized regression neural networks. Neurocomputing Francisco Martínez, Francisco Charte, María Pilar Frías, Ana María Martínez-Rodríguez
2021	J	`jnl`	ClEnDAE: A classifier based on ensembles with built-in dimensionality reduction through denoising autoencoders. Inf. Sci. Francisco Javier Pulgar, Francisco Charte, Antonio J. Rivera, María José del Jesus
2021	J	`jnl`	Reducing Data Complexity using Autoencoders with Class-informed Loss Functions. CoRR David Charte, Francisco Charte, Francisco Herrera
2021	Misc	`conf`	Slicer: Feature Learning for Class Separability with Least-Squares Support Vector Machine Loss and COVID-19 Chest X-Ray Case Study. HAIS David Charte, Iván Sevillano-García, María Jesús Lucena-González, José Luis Martín-Rodríguez, Francisco Charte, Francisco Herrera
2020	J	`jnl`	A Comprehensive and Didactic Review on Multilabel Learning Software Tools. IEEE Access Francisco Charte
2020	J	`jnl`	A Showcase of the Use of Autoencoders in Feature Learning Applications. CoRR David Charte, Francisco Charte, María José del Jesus, Francisco Herrera
2020	J	`jnl`	An analysis on the use of autoencoders for representation learning: Fundamentals, learning task case studies, explainability and challenges. Neurocomputing David Charte, Francisco Charte, María José del Jesus, Francisco Herrera
2020	J	`jnl`	An analysis on the use of autoencoders for representation learning: fundamentals, learning task case studies, explainability and challenges. CoRR David Charte, Francisco Charte, María José del Jesus, Francisco Herrera
2020	J	`jnl`	Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications. Neurocomputing Juan Manuel Górriz, Javier Ramírez, Andrés Ortiz, Francisco Jesús Martínez-Murcia, Fermín Segovia, John Suckling, Matthew Leming, Yu-Dong Zhang, José Ramón Álvarez Sánchez, Guido Bologna, María Paula Bonomini, Fernando E. Casado, David Charte, Francisco Charte, Ricardo Contreras, Alfredo Cuesta-Infante, Richard J. Duro, Antonio Fernández-Caballero, José Manuel Ferrández
2020	J	`jnl`	Choosing the proper autoencoder for feature fusion based on data complexity and classifiers: Analysis, tips and guidelines. Inf. Fusion Francisco Javier Pulgar, Francisco Charte, Antonio J. Rivera, María José del Jesus
2020	J	`jnl`	E2PAMEA: A fast evolutionary algorithm for extracting fuzzy emerging patterns in big data environments. Neurocomputing Ángel Miguel García-Vico, Francisco Charte, Pedro González, David A. Elizondo, Cristóbal José Carmona
2020	J	`jnl`	EvoAAA: An evolutionary methodology for automated neural autoencoder architecture search. Integr. Comput. Aided Eng. Francisco Charte, Antonio J. Rivera, Francisco Martínez, María José del Jesus
2019	—	`conf`	A Showcase of the Use of Autoencoders in Feature Learning Applications. IWINAC (2) David Charte, Francisco Charte, María José del Jesus, Francisco Herrera
2019	J	`jnl`	A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations. Prog. Artif. Intell. David Charte, Francisco Charte, Salvador García, Francisco Herrera
2019	J	`jnl`	AEkNN: An AutoEncoder kNN-Based Classifier With Built-in Dimensionality Reduction. Int. J. Comput. Intell. Syst. Francisco Javier Pulgar, Francisco Charte, Antonio J. Rivera, María José del Jesus
2019	—	`conf`	Automatic Time Series Forecasting with GRNN: A Comparison with Other Models. IWANN (1) Francisco Martínez, Francisco Charte, Antonio J. Rivera, María Pilar Frías
2019	—	`conf`	Automating Autoencoder Architecture Configuration: An Evolutionary Approach. IWINAC (1) Francisco Charte, Antonio J. Rivera, Francisco Martínez, María José del Jesus
2019	J	`jnl`	Dealing with difficult minority labels in imbalanced mutilabel data sets. Neurocomputing Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera
2019	J	`jnl`	REMEDIAL-HwR: Tackling multilabel imbalance through label decoupling and data resampling hybridization. Neurocomputing Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera
2019	J	`jnl`	Ruta: Implementations of neural autoencoders in R. Knowl. Based Syst. David Charte, Francisco Herrera, Francisco Charte
2019	J	`jnl`	Time Series Forecasting with KNN in R: the tsfknn Package. R J. Francisco Martínez, María Pilar Frías, Francisco Charte, Antonio J. Rivera
2019	J	`jnl`	predtoolsTS: R package for streamlining time series forecasting. Prog. Artif. Intell. Francisco Charte, Alberto Vico, María Dolores Pérez-Godoy, Antonio J. Rivera
2018	—	`conf`	A First Approach to Face Dimensionality Reduction Through Denoising Autoencoders. IDEAL (1) Francisco Javier Pulgar, Francisco Charte, Antonio J. Rivera, María José del Jesus
2018	J	`jnl`	A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines. CoRR David Charte, Francisco Charte, Salvador García, María José del Jesus, Francisco Herrera
2018	J	`jnl`	A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines. Inf. Fusion David Charte, Francisco Charte, Salvador García, María José del Jesus, Francisco Herrera
2018	J	`jnl`	A snapshot on nonstandard supervised learning problems: taxonomy, relationships and methods. CoRR David Charte, Francisco Charte, Salvador García, Francisco Herrera
2018	J	`jnl`	AEkNN: An AutoEncoder kNN-based classifier with built-in dimensionality reduction. CoRR Francisco Javier Pulgar, Francisco Charte, Antonio J. Rivera, María José del Jesus
2018	J	`jnl`	Dealing with Difficult Minority Labels in Imbalanced Mutilabel Data Sets. CoRR Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera
2018	J	`jnl`	Tackling Multilabel Imbalance through Label Decoupling and Data Resampling Hybridization. CoRR Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera
2018	J	`jnl`	Tips, guidelines and tools for managing multi-label datasets: The mldr.datasets R package and the Cometa data repository. Neurocomputing Francisco Charte, Antonio J. Rivera, David Charte, María José del Jesus, Francisco Herrera
2018	J	`jnl`	Tips, guidelines and tools for managing multi-label datasets: the mldr.datasets R package and the Cometa data repository. CoRR Francisco Charte, Antonio J. Rivera, David Charte, María José del Jesus, Francisco Herrera
2017	B	`conf`	A first approach towards a fuzzy decision tree for multilabel classification. FUZZ-IEEE Ronaldo C. Prati, Francisco Charte, Francisco Herrera
2017	J	`jnl`	Comparative analysis of data mining and response surface methodology predictive models for enzymatic hydrolysis of pretreated olive tree biomass. Comput. Chem. Eng. Francisco Charte, Inmaculada Romero, María Dolores Pérez-Godoy, Antonio J. Rivera, Eulogio Castro
2017	Misc	`conf`	On the Impact of Imbalanced Data in Convolutional Neural Networks Performance. HAIS Francisco Javier Pulgar, Antonio J. Rivera, Francisco Charte, María José del Jesus
2016	—	`book`	Multilabel Classification - Problem Analysis, Metrics and Techniques Francisco Herrera, Francisco Charte, Antonio J. Rivera, María José del Jesus
2016	Misc	`conf`	On the Impact of Dataset Complexity and Sampling Strategy in Multilabel Classifiers Performance. HAIS Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera
2016	Misc	`conf`	R Ultimate Multilabel Dataset Repository. HAIS Francisco Charte, David Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera
2016	J	`jnl`	Subgroup Discovery with Evolutionary Fuzzy Systems in R: The SDEFSR Package. R J. Ángel M. García, Francisco Charte, Pedro González, Cristóbal J. Carmona, María José del Jesus
2015	J	`jnl`	Addressing imbalance in multilabel classification: Measures and random resampling algorithms. Neurocomputing Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera
2015	—	`conf`	CO ^2 RBFN-CS: First Approach Introducing Cost-Sensitivity in the Cooperative-Competitive RBFN Design. IWANN (1) María Dolores Pérez-Godoy, Antonio Jesús Rivera, Francisco Charte, María José del Jesus
2015	J	`jnl`	MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation. Knowl. Based Syst. Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera
2015	—	`conf`	QUINTA: A question tagging assistant to improve the answering ratio in electronic forums. EUROCON Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera
2015	Misc	`conf`	Resampling Multilabel Datasets by Decoupling Highly Imbalanced Labels. HAIS Francisco Charte, Antonio Jesús Rivera, María José del Jesus, Francisco Herrera
2015	J	`jnl`	Working with Multilabel Datasets in R: The mldr Package. R J. Francisco Charte, David Charte
2014	Misc	`conf`	Concurrence among Imbalanced Labels and Its Influence on Multilabel Resampling Algorithms. HAIS Francisco Charte, Antonio Jesús Rivera Rivas, María José del Jesus, Francisco Herrera
2014	J	`jnl`	LI-MLC: A Label Inference Methodology for Addressing High Dimensionality in the Label Space for Multilabel Classification. IEEE Trans. Neural Networks Learn. Syst. Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera
2014	C	`conf`	MLeNN: A First Approach to Heuristic Multilabel Undersampling. IDEAL Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera
2013	Misc	`conf`	A First Approach to Deal with Imbalance in Multi-label Datasets. HAIS Francisco Charte, Antonio Jesús Rivera Rivas, María José del Jesus, Francisco Herrera
2012	—	`conf`	Improving Multi-label Classifiers via Label Reduction with Association Rules. HAIS (2) Francisco Charte, Antonio Jesús Rivera Rivas, María José del Jesus, Francisco Herrera
2011	—	`conf`	Multi-label Testing for CO IWANN (1) Antonio Jesús Rivera Rivas, Francisco Charte, M. Dolores Pérez-Godoy, María José del Jesus