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2018

Reyes, O; Cano, A; Fardoun, H; Ventura, S

A locally weighted learning method based on a data gravitation model for multi-target regression Journal Article

International Journal of Computational Intelligence Systems, 11 (1), pp. 282-295, 2018.

BibTeX | Tags: Multi-label Learning, Supervised Learning

Moyano, J M; Gibaja, E; Cios, K J; Ventura, S

Review of ensembles of multi-label classifiers: Models, experimental study and prospects Journal Article

Information Fusion, 44 , pp. 33 - 45, 2018, ISSN: 1566-2535.

Links | BibTeX | Tags: Classification, Multi-label Learning, Supervised Learning

Skryjomski, P; Krawczyk, B; Cano, A

Speeding up k-Nearest Neighbors Classifier for Large-Scale Multi-Label Learning on GPUs Journal Article

Neurocomputing, In press , 2018.

BibTeX | Tags: Classification, GP-GPU, Multi-label Learning, Scalability

Gonzalez-Lopez, J; Ventura, S; Cano, A

Distributed Nearest Neighbor Classification for Large-Scale Multi-label Data on Spark Journal Article

Future Generation Computer Systems, 87 , pp. 66-82, 2018.

Links | BibTeX | Tags: Classification, Multi-label Learning, Spark

Roseberry, M; Cano, A

Multi-label kNN Classifier with Self Adjusting Memory for Drifting Data Streams Inproceedings

LIDTA@PKDD/ECML, 2018.

BibTeX | Tags: Classification, Multi-label Learning

Moyano, J M; Gibaja, E; Cios, K J; Ventura, S

An evolutionary approach to build ensembles of multi-label classifiers Journal Article

Information Fusion, 2018, ISSN: 1566-2535.

Links | BibTeX | Tags: Classification, Evolutionary Algorithms, Multi-label Learning, Supervised Learning

Reyes, O; Moyano, J M; Luna, J M; Ventura, S

Resolviendo el problema de regresión multi-salida mediante Gene Expression Programming Inproceedings

XVIII Conferencia de la Asociación Española para la Inteligencia Artificial, CAEPIA 2018, pp. 907–912, 2018.

Links | BibTeX | Tags: Evolutionary Algorithms, Gene Expression Programming (GEP), Multi-label Learning

Reyes, O; Moyano, J M; Luna, J M; Ventura, S

A gene expression programming method for multi-target regression Inproceedings

Proceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications, LOPAL 2018, Rabat, Morocco, May 2-5, 2018., pp. 2:1–2:6, 2018.

Links | BibTeX | Tags: Evolutionary Algorithms, Gene Expression Programming (GEP), Multi-label Learning

Reyes, O; Ventura, S

Evolutionary Strategy to perform Batch-Mode Active Learning on Multi-Label Data Journal Article

ACM Transactions on Intelligent Systems and Technology, 9 (4), pp. 46–1, 2018.

Links | BibTeX | Tags: Active Learning, Evolutionary Algorithms, Multi-label Learning

2017

Moyano, J M; Gibaja, E; Ventura, S

An evolutionary algorithm for optimizing the target ordering in Ensemble of Regressor Chains Inproceedings

2017 IEEE Congress on Evolutionary Computation (CEC), pp. 2015-2021, 2017.

Links | BibTeX | Tags: Evolutionary Algorithms, Multi-label Learning, Supervised Learning

Gonzalez-Lopez, J; Cano, A; Ventura, S

Large-scale multi-label ensemble learning on Spark Inproceedings

Proceedings of the 11th IEEE International Conference On Big Data Science And Engineering, pp. 893-900, 2017.

BibTeX | Tags: Multi-label Learning, Scalability, Spark

Melki, G; Cano, A; Kecman, V; Ventura, S

Multi-Target Support Vector Regression Via Correlation Regressor Chains Journal Article

Information Sciences, 415-416 , pp. 53-69, 2017.

Links | BibTeX | Tags: Multi-label Learning, Supervised Learning

Moyano, J M; Gibaja, E; Ventura, S

MLDA: A tool for analyzing multi-label datasets Journal Article

Knowledge-Based Systems, 121 , pp. 1-3, 2017, ISSN: 0950-7051.

Links | BibTeX | Tags: Data Mining Software, Data Preprocessing, Multi-label Learning, Multi-view Learning

Reyes, O; Morell, C; Ventura, S

Effective active learning strategy for multi-label learning Journal Article

Neurocomputing, In Press, 2017.

Links | BibTeX | Tags: Active Learning, Multi-label Learning

2016

Cano, A; Luna, J M; Gibaja, E; Ventura, S

LAIM discretization for multi-label data Journal Article

Information Sciences, 330 , pp. 370–384, 2016.

Links | BibTeX | Tags: Multi-label Learning

Gibaja, E; Moyano, J M; Ventura, S

An ensemble-based approach for multi-view multi-label classification Journal Article

Progress in Artificial Intelligence, 5 (4), pp. 251–259, 2016, ISSN: 2192-6360.

Links | BibTeX | Tags: Classification, Multi-label Learning, Multi-view Learning

Moyano, J M; Gibaja, E; Ventura, S

Una herramienta para analizar conjuntos de datos multi-etiqueta Inproceedings

XVII Conferencia de la Asociación Española para la Inteligencia Artificial, CAEPIA '16, pp. 857–866, 2016, ISBN: 978-84-9012-632-5.

Links | BibTeX | Tags: Data Preprocessing, Feature Selection, Instance Selection, Multi-label Learning, Multi-view Learning, Software Design and Development

Reyes, O; Morell, C; Ventura, S

Effective lazy learning algorithm based on a data gravitation model for multi-label learning Journal Article

Information Sciences, 340 (341), pp. 159-174, 2016.

Links | BibTeX | Tags: Multi-label Learning, Supervised Learning

Reyes, O; Ventura, S

Estrategia efectiva para el aprendizaje activo multi-etiqueta Inproceedings

XVII Conferencia de la Asociación Española para la Inteligencia Artificial, pp. 835-844, 2016.

BibTeX | Tags: Active Learning, Multi-label Learning

2015

Gibaja, E; Ventura, S

A Tutorial on Multilabel Learning Journal Article

ACM Comput. Surv., 47 (3), pp. 52, 2015.

Links | BibTeX | Tags: Classification, Multi-label Learning

Gibaja, E; Moyano, J M; Ventura, S

Combinación de vistas para clasificación multi-etiqueta: estudio preliminar Inproceedings

XVI Conferencia de la Asociación Española para la Inteligencia Artificial, CAEPIA'15, pp. 759–768, 2015.

Links | BibTeX | Tags: Classification, Multi-label Learning, Multi-view Learning

Moyano, J M; Gibaja, E; Cano, A; Luna, J M; Ventura, S

Diseño automático de multi-clasificadores basados en proyecciones de etiquetas Inproceedings

XVI Conferencia de la Asociación Española para la Inteligencia Artificial, pp. 355–365, 2015.

Links | BibTeX | Tags: Classification, Evolutionary Algorithms, Multi-label Learning, Supervised Learning

Moyano, J M; Gibaja, E; Cano, A; Luna, J M; Ventura, S

Algoritmo evolutivo para optimizar ensembles de clasificadores multi-etiqueta Inproceedings

X Congreso Español sobre Metaheurísticas and Algoritmos Evolutivos y Bioinspirados, pp. 219-225, 2015.

Links | BibTeX | Tags: Classification, Evolutionary Algorithms, Multi-label Learning, Supervised Learning

Reyes, O; Morell, C; Ventura, S

Scalable extensions of the ReliefF algorithm for weighting and selecting features on the multi-label learning context Journal Article

Neurocomputing, 161 , pp. 168–182, 2015.

Links | BibTeX | Tags: Data Preprocessing, Feature Selection, Multi-label Learning, Supervised Learning

2014

Gibaja, E; Ventura, S

Multi-label learning: A review of the state of the art and ongoing research Journal Article

Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 4 (6), pp. 411-444, 2014.

Links | BibTeX | Tags: Classification, Multi-label Learning

Reyes, O; Morell, C; Ventura, S

Evolutionary feature weighting to improve the performance of multi-label lazy algorithms Journal Article

Integrated Computer-Aided Engineering, 21 (4), pp. 339-354, 2014.

Links | BibTeX | Tags: Data Preprocessing, Evolutionary Algorithms, Multi-label Learning, Supervised Learning

2013

Cano, A; Zafra, A; Gibaja, E; Ventura, S

A grammar-guided genetic programming algorithm for multi-label classification Journal Article

7831 LNCS , pp. 217-228, 2013.

Links | BibTeX | Tags: Classification, Genetic Programming, Multi-label Learning

Reyes, O; Morell, C; Ventura, S

ReliefF-ML: An Extension of ReliefF Algorithm to Multi-label Learning Inproceedings

Ruiz-Shulcloper, J; Sanniti di Baja, G (Ed.): Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 18th Iberoamerican Congress (CIARP-2013), Havana, Cuba, November 20-23, 2013, Proceedings, Part II, pp. 528-535, Springer Berlin Heidelberg, 2013.

Links | BibTeX | Tags: Data Preprocessing, Multi-label Learning, Supervised Learning

Reyes, O; Morell, C; Ventura, S

Feature weighting on multi-label data through quadratic loss minimization Inproceedings

Congreso Internacional de Matemática y Computación (COMPUMAT-2013), 2013.

Links | BibTeX | Tags: Data Preprocessing, Evolutionary Algorithms, Multi-label Learning, Supervised Learning

2012

Reyes, O; Morell, C; Ventura, S

Learning similarity metric to improve the performance of lazy multi-label ranking algorithms Inproceedings

Proceedings of the 12th International Conference on Intelligent Systems Design and Applications, ISDA'12, pp. 246-251, 2012.

Links | BibTeX | Tags: Data Preprocessing, Evolutionary Algorithms, Multi-label Learning, Supervised Learning

2011

Ávila, J L; Gibaja, E; Zafra, A; Ventura, S

A Gene Expression Programming Algorithm for Multi-Label Classification Journal Article

Multiple-Valued Logic and Soft Computing, 17 (2-3), pp. 183–206, 2011.

Links | BibTeX | Tags: Classification, Discriminant Functions, Gene Expression Programming (GEP), Multi-label Learning

2010

Ávila, J L; Gibaja, E; Ventura, S

Evolving multi-label classification rules with gene expression programming: a preliminary study Inproceedings

International Conference on Hybrid Artificial Intelligence Systems, pp. 9–16, Springer 2010.

BibTeX | Tags: Classification, Classification Rules, Gene Expression Programming (GEP), Multi-label Learning

Gibaja, E; Victoriano, M; Ávila, J L; Ventura, S

A TDIDT technique for multi-label classification Inproceedings

Proceedings of the 10th International Conference on Intelligent Systems Design and Applications, ISDA'10, pp. 519-524, 2010.

Links | BibTeX | Tags: Classification, Multi-label Learning

2009

Ávila, J L; Gibaja, E; Ventura, S

Multi-label classification with gene expression programming Inproceedings

International Conference on Hybrid Artificial Intelligence Systems, pp. 629–637, Springer 2009.

BibTeX | Tags: Classification, Discriminant Functions, Gene Expression Programming (GEP), Multi-label Learning

Ávila, J L; Gibaja, E; Zafra, A; Ventura, S

A niching algorithm to learn discriminant functions with multi-label patterns Inproceedings

International Conference on Intelligent Data Engineering and Automated Learning, pp. 570–577, Springer 2009.

BibTeX | Tags: Classification, Discriminant Functions, Gene Expression Programming (GEP), Multi-label Learning