‪Francisco Charte (ORCID:0000-0002-3083-8942)‬

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María José Del Jesus DíazAssociate professor of Computer Science, University of JaénPotvrđena adresa e-pošte na ujaen.es
Antonio J. RiveraProfesor de Ingeniería Informática (Universidad de Jaén)Potvrđena adresa e-pošte na ujaen.es
Francisco HerreraProfessor Computer Science and AI, DaSCI Research Institute, Granada University, SpainPotvrđena adresa e-pošte na decsai.ugr.es
Francisco Javier Pulgar RubioUniversidad de JaénPotvrđena adresa e-pošte na ujaen.es
María Dolores Pérez GodoyProfesor de Informática (UJA)Potvrđena adresa e-pošte na ujaen.es
Salvador GarcíaFull Professor of Computer Science and Artificial Intelligence. University of Granada.Potvrđena adresa e-pošte na decsai.ugr.es
David CharteUniversidad de GranadaPotvrđena adresa e-pošte na ugr.es
Macarena Espinilla-EstévezUniversity of JaénPotvrđena adresa e-pošte na ujaen.es
David Elizondo, D. Elizondo, D. A. Eliz...De Montfort University, University of Georgia, Universite Louis PasteurPotvrđena adresa e-pošte na dmu.ac.uk
Cristóbal J. CarmonaFull Professor at University of JaenPotvrđena adresa e-pošte na ujaen.es
G. NofuentesUniversity of JaénPotvrđena adresa e-pošte na ujaen.es
Ana María Martínez RodríguezProfesor de Estadística, Universidad de JaénPotvrđena adresa e-pošte na ujaen.es
Ángel M. García-VicoUniversidad de JaénPotvrđena adresa e-pošte na ujaen.es
Eulogio CastroProfessor of Chemical Engineering, University of JaenPotvrđena adresa e-pošte na ujaen.es
Javi Medina QueroAssociate professor, University of GranadaPotvrđena adresa e-pošte na ugr.es
Julián Luengo MartínAssociate Professor at University of GranadaPotvrđena adresa e-pošte na decsai.ugr.es
Ronaldo C. PratiAssociate Professor of Computer Science, Universidade Federal do ABCPotvrđena adresa e-pošte na ufabc.edu.br
Pedro González GarcíaUniversidad de JaénPotvrđena adresa e-pošte na ujaen.es
Lina García-CabreraProfesora del Departamento de Informática, EPS, Universidad de JaénPotvrđena adresa e-pošte na ujaen.es
José Luis López RuizAssistant Professor at the University of JaénPotvrđena adresa e-pošte na ujaen.es

Prati

Francisco Charte (ORCID:0000-0002-3083-8942)

Associate Professor at Computer Science Dept. Universidad de Jaén

Potvrđena adresa e-pošte na ujaen.es - Početna stranica

Multi-label learning Representation learning Self-supervised learning


Naslov Poredaj po navodima Poredaj po godini Poredaj po naslovu	Citirano Citirano	Godina
Multilabel classification F Herrera, F Charte, AJ Rivera, MJ Del Jesus Multilabel Classification, 17-31, 2016	405	2016
A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines D Charte, F Charte, S García, MJ del Jesus, F Herrera IX Simposio de Teoría y Aplicaciones de la Minería de Datos; XVIII …, 2018	371	2018
A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines D Charte, F Charte, S García, MJ del Jesus, F Herrera Information Fusion 44, 78--96, 2018	371	2018
Addressing imbalance in multilabel classification: Measures and random resampling algorithms F Charte, AJ Rivera, MJ del Jesus, F Herrera Neurocomputing 163, 3-16, 2015	313	2015
Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications JM Górriz, J Ramírez, A Ortíz, FJ Martínez-Murcia, F Segovia, J Suckling, ... Neurocomputing 410, 237-270, 2020	304	2020
MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation F Charte, AJ Rivera, MJ del Jesus, F Herrera Knowledge-Based Systems 89, 385-397, 2015	278	2015
A first approach to deal with imbalance in multi-label datasets F Charte, A Rivera, MJ del Jesus, F Herrera International Conference on Hybrid Artificial Intelligence Systems, 150-160, 2013	120	2013
Working with Multilabel Datasets in R: The mldr Package F Charte, D Charte The R Journal 7 (2), 14, 2015	91	2015
An analysis on the use of autoencoders for representation learning: Fundamentals, learning task case studies, explainability and challenges D Charte, F Charte, MJ del Jesus, F Herrera Neurocomputing 404, 93-107, 2020	83	2020
Dealing with difficult minority labels in imbalanced mutilabel data sets F Charte, AJ Rivera, MJ del Jesus, F Herrera Neurocomputing 326, 39-53, 2019	69	2019
Is the average photon energy a unique characteristic of the spectral distribution of global irradiance? G Nofuentes, CA Gueymard, J Aguilera, MD Pérez-Godoy, F Charte Solar Energy 149, 32-43, 2017	69	2017
MLeNN: a first approach to heuristic multilabel undersampling F Charte, AJ Rivera, MJ del Jesus, F Herrera International Conference on Intelligent Data Engineering and Automated …, 2014	66	2014
Strategies for time series forecasting with generalized regression neural networks F Martínez, F Charte, MP Frías, AM Martínez-Rodríguez Neurocomputing 491, 509-521, 2022	63	2022
Concurrence among imbalanced labels and its influence on multilabel resampling algorithms F Charte, A Rivera, MJ del Jesus, F Herrera International Conference on Hybrid Artificial Intelligence Systems, 110-121, 2014	61	2014
Time Series Forecasting with KNN in R: the tsfknn Package F Martínez, MP Frías, F Charte, AJ Rivera The R Journal 11 (2), 229-242, 2019	50	2019
REMEDIAL-HwR: Tackling multilabel imbalance through label decoupling and data resampling hybridization F Charte, AJ Rivera, MJ del Jesus, F Herrera Neurocomputing 326, 110-122, 2019	49	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 Information Fusion 54, 44-60, 2020	42	2020
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 IEEE Transactions on Neural Networks and Learning Systems 25 (10), 1842-1854, 2014	42	2014
QUINTA: a question tagging assistant to improve the answering ratio in electronic forums F Charte, AJ Rivera, MJ del Jesus, F Herrera IEEE EUROCON 2015-International Conference on Computer as a Tool (EUROCON), 1-6, 2015	39	2015
A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations D Charte, F Charte, S García, F Herrera Progress in Artificial Intelligence, 1-14, 2018	38	2018

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