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ORCIDAntonio J. Rivera
- > Home > Persons > Antonio J. Rivera
Publications
- 2024
[j31]María Dolores Pérez-Godoy, Marta Molina, Francisco Martínez, David A. Elizondo, Francisco Charte, Antonio J. Rivera:
DESReg: Dynamic Ensemble Selection library for Regression tasks. Neurocomputing 580: 127487 (2024)- 2023
- [j30]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:
XAIRE: An ensemble-based methodology for determining the relative importance of variables in regression tasks. Application to a hospital emergency department. Artif. Intell. Medicine 137: 102494 (2023) - [j29]Antonio J. Rivera, Miguel A. Dávila, David A. Elizondo, María José del Jesus, Francisco Charte:
mldr.resampling: Efficient reference implementations of multilabel resampling algorithms. Neurocomputing 559: 126806 (2023) - [c37]Maria Isabel Cabrera-Bermejo, María José del Jesus, Antonio J. Rivera, David A. Elizondo, Francisco Charte, M. Dolores Pérez-Godoy:
Analysis of Transformer Model Applications. HAIS 2023: 231-243 - [c36]David de la Rosa, Antonio Álvarez, Ramón Pérez, Germán Garrote, Antonio J. Rivera, María José del Jesus, Francisco Charte:
NOSpcimen: A First Approach to Unsupervised Discarding of Empty Photo Trap Images. IWANN (2) 2023: 39-51 - [i7]Francisco Charte, Antonio J. Rivera, Francisco Martínez, María José del Jesus:
EvoAAA: An evolutionary methodology for automated \neural autoencoder architecture search. CoRR abs/2301.06047 (2023) - [i6]Antonio J. Rivera, Miguel A. Dávila, David A. Elizondo, María José del Jesus, Francisco Charte:
mldr.resampling: Efficient Reference Implementations of Multilabel Resampling Algorithms. CoRR abs/2305.17152 (2023) - [i5]David de la Rosa, Antonio J. Rivera, María José del Jesus, Francisco Charte:
PARDINUS: Weakly supervised discarding of photo-trapping empty images based on autoencoders. CoRR abs/2312.14812 (2023) - 2021
- [j26]Francisco Javier Pulgar, Francisco Charte, Antonio J. Rivera, María José del Jesus:
ClEnDAE: A classifier based on ensembles with built-in dimensionality reduction through denoising autoencoders. Inf. Sci. 565: 146-176 (2021) - 2020
- [j25]Francisco Charte, Antonio J. Rivera, Francisco Martínez, María José del Jesus:
EvoAAA: An evolutionary methodology for automated neural autoencoder architecture search. Integr. Comput. Aided Eng. 27(3): 211-231 (2020) - [j24]Francisco Javier Pulgar, Francisco Charte, Antonio J. Rivera, María José del Jesus:
Choosing the proper autoencoder for feature fusion based on data complexity and classifiers: Analysis, tips and guidelines. Inf. Fusion 54: 44-60 (2020) - 2019
- [j22]Francisco Javier Pulgar, Francisco Charte, Antonio J. Rivera, María José del Jesus:
AEkNN: An AutoEncoder kNN-Based Classifier With Built-in Dimensionality Reduction. Int. J. Comput. Intell. Syst. 12(1): 436-452 (2019) - [j21]Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera:
Dealing with difficult minority labels in imbalanced mutilabel data sets. Neurocomputing 326-327: 39-53 (2019) - [j20]Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera:
REMEDIAL-HwR: Tackling multilabel imbalance through label decoupling and data resampling hybridization. Neurocomputing 326-327: 110-122 (2019) - [j19]Francisco Charte, Alberto Vico, María Dolores Pérez-Godoy, Antonio J. Rivera:
predtoolsTS: R package for streamlining time series forecasting. Prog. Artif. Intell. 8(4): 505-510 (2019) - [j18]Francisco Martínez, María Pilar Frías, Francisco Charte, Antonio J. Rivera:
Time Series Forecasting with KNN in R: the tsfknn Package. R J. 11(2): 229 (2019) - [c34]Francisco Martínez, Francisco Charte, Antonio J. Rivera, María Pilar Frías:
Automatic Time Series Forecasting with GRNN: A Comparison with Other Models. IWANN (1) 2019: 198-209 - [c33]Daniel Trujillo Viedma, Antonio Jesús Rivera Rivas, Francisco Charte Ojeda, María José del Jesus Díaz:
A First Approximation to the Effects of Classical Time Series Preprocessing Methods on LSTM Accuracy. IWANN (1) 2019: 270-280 - [c32]Francisco Charte, Antonio J. Rivera, Francisco Martínez, María José del Jesus:
Automating Autoencoder Architecture Configuration: An Evolutionary Approach. IWINAC (1) 2019: 339-349 - 2018
- [j16]Francisco Charte, Antonio J. Rivera, David Charte, María José del Jesus, Francisco Herrera:
Tips, guidelines and tools for managing multi-label datasets: The mldr.datasets R package and the Cometa data repository. Neurocomputing 289: 68-85 (2018) - [c31]Francisco Javier Pulgar, Francisco Charte, Antonio J. Rivera, María José del Jesus:
A First Approach to Face Dimensionality Reduction Through Denoising Autoencoders. IDEAL (1) 2018: 439-447 - [c30]Daniel Trujillo Viedma, Antonio Jesús Rivera Rivas, Francisco Charte Ojeda, María José del Jesus Díaz:
An Approximation to Deep Learning Touristic-Related Time Series Forecasting. IDEAL (1) 2018: 448-456 - [i4]Francisco Charte, Antonio J. Rivera, David Charte, María José del Jesus, Francisco Herrera:
Tips, guidelines and tools for managing multi-label datasets: the mldr.datasets R package and the Cometa data repository. CoRR abs/1802.03568 (2018) - [i3]Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera:
Tackling Multilabel Imbalance through Label Decoupling and Data Resampling Hybridization. CoRR abs/1802.05031 (2018) - [i2]Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera:
Dealing with Difficult Minority Labels in Imbalanced Mutilabel Data Sets. CoRR abs/1802.05033 (2018) - [i1]Francisco Javier Pulgar, Francisco Charte, Antonio J. Rivera, María José del Jesus:
AEkNN: An AutoEncoder kNN-based classifier with built-in dimensionality reduction. CoRR abs/1802.08465 (2018) - 2017
- [j15]Francisco Charte, Inmaculada Romero, María Dolores Pérez-Godoy, Antonio J. Rivera, Eulogio Castro:
Comparative analysis of data mining and response surface methodology predictive models for enzymatic hydrolysis of pretreated olive tree biomass. Comput. Chem. Eng. 101: 23-30 (2017) - [c29]Francisco Javier Pulgar, Antonio J. Rivera, Francisco Charte, María José del Jesus:
On the Impact of Imbalanced Data in Convolutional Neural Networks Performance. HAIS 2017: 220-232 - [c28]Antonio Jesús Rivera Rivas, Francisco Charte Ojeda, Francisco Javier Pulgar, María José del Jesus:
A Transformation Approach Towards Big Data Multilabel Decision Trees. IWANN (1) 2017: 73-84 - [c27]Francisco Charte Ojeda, Inmaculada Romero, Antonio Jesús Rivera Rivas, Eulogio Castro:
Modeling the Transformation of Olive Tree Biomass into Bioethanol with Reg-CO ^2 RBFN. IWANN (1) 2017: 733-744 - 2016
- [b1]Francisco Herrera, Francisco Charte, Antonio J. Rivera, María José del Jesus:
Multilabel Classification - Problem Analysis, Metrics and Techniques. Springer 2016, ISBN 978-3-319-41110-1, pp. 1-194 - [c25]Francisco Charte, David Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera:
R Ultimate Multilabel Dataset Repository. HAIS 2016: 487-499 - [c24]Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera:
On the Impact of Dataset Complexity and Sampling Strategy in Multilabel Classifiers Performance. HAIS 2016: 500-511 - 2015
- [j12]Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera:
Addressing imbalance in multilabel classification: Measures and random resampling algorithms. Neurocomputing 163: 3-16 (2015) - [j11]Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera:
MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation. Knowl. Based Syst. 89: 385-397 (2015) - [c22]Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera:
QUINTA: A question tagging assistant to improve the answering ratio in electronic forums. EUROCON 2015: 1-6 - [c21]Francisco Charte, Antonio Jesús Rivera, María José del Jesus, Francisco Herrera:
Resampling Multilabel Datasets by Decoupling Highly Imbalanced Labels. HAIS 2015: 489-501 - [c20]María Dolores Pérez-Godoy, Antonio Jesús Rivera, Francisco Charte, María José del Jesus:
CO ^2 RBFN-CS: First Approach Introducing Cost-Sensitivity in the Cooperative-Competitive RBFN Design. IWANN (1) 2015: 361-373 - 2014
- [j9]Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera:
LI-MLC: A Label Inference Methodology for Addressing High Dimensionality in the Label Space for Multilabel Classification. IEEE Trans. Neural Networks Learn. Syst. 25(10): 1842-1854 (2014) - [c19]Francisco Charte, Antonio Jesús Rivera Rivas, María José del Jesus, Francisco Herrera:
Concurrence among Imbalanced Labels and Its Influence on Multilabel Resampling Algorithms. HAIS 2014: 110-121 - [c18]Francisco Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera:
MLeNN: A First Approach to Heuristic Multilabel Undersampling. IDEAL 2014: 1-9 - 2013
- [c17]Francisco Charte, Antonio Jesús Rivera Rivas, María José del Jesus, Francisco Herrera:
A First Approach to Deal with Imbalance in Multi-label Datasets. HAIS 2013: 150-160 - [c15]Francisco Charte Ojeda, Antonio Jesús Rivera Rivas, María Dolores Pérez-Godoy, María José del Jesus:
Alternative OVA Proposals for Cooperative Competitive RBFN Design in Classification Tasks. IWANN (1) 2013: 331-338 - 2012
- [c14]Francisco Charte, Antonio Jesús Rivera Rivas, María José del Jesus, Francisco Herrera:
Improving Multi-label Classifiers via Label Reduction with Association Rules. HAIS (2) 2012: 188-199 - 2011
- [c11]Antonio Jesús Rivera Rivas, Francisco Charte, M. Dolores Pérez-Godoy, María José del Jesus:
Multi-label Testing for CO2RBFN: A First Approach to the Problem Transformation Methodology for Multi-label Classification. IWANN (1) 2011: 41-48
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last updated on 2024-07-12 20:14 CEST by the dblp team
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