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José Miguel Puerta
José Miguel Puerta Callejón
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- affiliation: University of Castilla-La Mancha, Albacete, Spain
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2020 – today
- 2024
- [j41]Jorge D. Laborda
, Pablo Torrijos, José Miguel Puerta, José A. Gámez:
Distributed fusion-based algorithms for learning high-dimensional Bayesian Networks: Testing ring and star topologies. Int. J. Approx. Reason. 175: 109302 (2024) - [j40]Jorge D. Laborda
Parallel structural learning of Bayesian networks: Iterative divide and conquer algorithm based on structural fusion. Knowl. Based Syst. 296: 111840 (2024) - [j39]Luis Gonzalez-Naharro, M. Julia Flores, Jesus Martínez-Gómez, José Miguel Puerta:
Evaluation of data augmentation techniques on subjective tasks. Mach. Vis. Appl. 35(4): 99 (2024) - [c55]Pablo Torrijos, José A. Gámez, José Miguel Puerta:
Structural Fusion of Bayesian Networks with Limited Treewidth Using Genetic Algorithms. CEC 2024: 1-8 - [c54]Guillermo Fernández, José A. Gámez, José Miguel Puerta, Juan A. Aledo, Jose Maria Alonso-Moral, Alberto Bugarín:
A User Study on the Utility of Context-Aware Explanations for Assisting Data Scientists in Error Analysis of Fuzzy Decision Trees. FUZZ 2024: 1-8 - [c53]Guillermo Fernández
FLocalX - Local to Global Fuzzy Explanations for Black Box Classifiers. IDA (2) 2024: 197-209 - [c52]Pablo Torrijos
Federated Learning with Discriminative Naive Bayes Classifier. IDEAL (2) 2024: 328-339 - [i3]Jorge D. Laborda, Pablo Torrijos, José Miguel Puerta, José A. Gámez:
A Ring-Based Distributed Algorithm for Learning High-Dimensional Bayesian Networks. CoRR abs/2409.13314 (2024) - [i2]Ricardo Montañana, José A. Gámez, José Miguel Puerta:
ODTE - An ensemble of multi-class SVM-based oblique decision trees. CoRR abs/2411.13376 (2024) - 2023
- [j38]Luis Gonzalez-Naharro
Novel groundtruth transformations for the aesthetic assessment problem. Inf. Process. Manag. 60(4): 103368 (2023) - [c51]Pablo Torrijos
MiniAnDE: A Reduced AnDE Ensemble to Deal with Microarray Data. EANN 2023: 131-143 - [c50]Jorge D. Laborda
A Ring-Based Distributed Algorithm for Learning High-Dimensional Bayesian Networks. ECSQARU 2023: 123-135 - [i1]Pablo Torrijos, José A. Gámez, José Miguel Puerta:
MiniAnDE: a reduced AnDE ensemble to deal with microarray data. CoRR abs/2311.12879 (2023) - 2022
- [j37]Fernando Rubio
Ranking-based scores for the assessment of aesthetic quality in photography. Signal Process. Image Commun. 108: 116803 (2022) - [j36]Guillermo Fernández
Factual and Counterfactual Explanations in Fuzzy Classification Trees. IEEE Trans. Fuzzy Syst. 30(12): 5484-5495 (2022) - 2021
- [j35]Fernando Rubio Perona
An Application for Aesthetic Quality Assessment in Photography with Interpretability Features. Entropy 23(11): 1389 (2021) - [j34]José Miguel Puerta, Juan A. Aledo, José A. Gámez
Efficient and accurate structural fusion of Bayesian networks. Inf. Fusion 66: 155-169 (2021) - [c49]Ricardo Montañana
STree: A Single Multi-class Oblique Decision Tree Based on Support Vector Machines. CAEPIA 2021: 54-64
2010 – 2019
- 2019
- [c48]José Miguel Puerta, Juan A. Aledo
Structural Fusion/Aggregation of Bayesian Networks via Greedy Equivalence Search Learning Algorithm. ECSQARU 2019: 432-443 - [c47]Luis de la Ossa, Pablo Bermejo, Juan A. Aledo
CiDAEN: An Online Data Science Course. HELMeTO 2019: 113-124 - 2018
- [j33]Juan Ignacio Alonso-Barba, Luis de la Ossa
On the use of local search heuristics to improve GES-based Bayesian network learning. Appl. Soft Comput. 64: 366-376 (2018) - [j32]Pablo Bermejo
Adapting the CMIM algorithm for multilabel feature selection. A comparison with existing methods. Expert Syst. J. Knowl. Eng. 35(1) (2018) - [c46]Jacinto Arias, José A. Gámez, José Miguel Puerta:
Bayesian Network Classifiers Under the Ensemble Perspective. PGM 2018: 1-12 - 2017
- [j31]Javier Cózar, José Miguel Puerta, José A. Gámez:
An Application of Dynamic Bayesian Networks to Condition Monitoring and Fault Prediction in a Sensored System: a Case Study. Int. J. Comput. Intell. Syst. 10(1): 176-195 (2017) - [j30]José A. Gámez, Francisco Herrera, José Miguel Puerta:
Guest Editorial: Recent Trends in Intelligent Systems. Int. J. Intell. Syst. 32(2): 107-108 (2017) - [j29]Amparo Alonso-Betanzos, José A. Gámez, Francisco Herrera, José Miguel Puerta, José C. Riquelme:
Volume, variety and velocity in Data Science. Knowl. Based Syst. 117: 1-2 (2017) - [j28]Jacinto Arias
Learning distributed discrete Bayesian Network Classifiers under MapReduce with Apache Spark. Knowl. Based Syst. 117: 16-26 (2017) - [j27]Fernando Rubio, Jesus Martínez-Gómez
Integration of contextual information into the scene classification problem. Robotics Auton. Syst. 97: 171-181 (2017) - [j26]Antonio Jesús Díaz-Honrubia
CTU splitting algorithm for H.264/AVC and HEVC simultaneous encoding. J. Supercomput. 73(1): 190-202 (2017) - [c45]Rafael Rivera-López
OC1-DE: A Differential Evolution Based Approach for Inducing Oblique Decision Trees. ICAISC (1) 2017: 427-438 - [c44]Fernando Rubio
Drawing a baseline in aesthetic quality assessment. ICMV 2017: 106961M - 2016
- [j25]Fernando Rubio
Comparison between Bayesian network classifiers and SVMs for semantic localization. Expert Syst. Appl. 64: 434-443 (2016) - [j24]Jacinto Arias, José A. Gámez
A scalable pairwise class interaction framework for multidimensional classification. Int. J. Approx. Reason. 68: 194-210 (2016) - [j23]Antonio Jesús Díaz-Honrubia
Low-complexity heterogeneous architecture for H.264/HEVC video transcoding. J. Real Time Image Process. 12(2): 311-327 (2016) - [j22]Antonio Jesús Díaz-Honrubia
Adaptive Fast Quadtree Level Decision Algorithm for H.264 to HEVC Video Transcoding. IEEE Trans. Circuits Syst. Video Technol. 26(1): 154-168 (2016) - [c43]Pablo Bermejo, José A. Gámez, José Miguel Puerta, Marco A. Esquivias, Pedro J. Tárraga:
Construction of a Semi-Naive Model to Predict Early Readmission of COPD Patients by Using Quality Care Information. ICDM Workshops 2016: 233-240 - 2015
- [j21]Sara Sáez-Atienzar
Automatic quantification of the subcellular localization of chimeric GFP protein supported by a two-level Naive Bayes classifier. Expert Syst. Appl. 42(3): 1531-1537 (2015) - [j20]Jacinto Arias, José A. Gámez
Structural Learning of Bayesian Networks Via Constrained Hill Climbing Algorithms: Adjusting Trade-off between Efficiency and Accuracy. Int. J. Intell. Syst. 30(3): 292-325 (2015) - [c42]Antonio Jesús Díaz-Honrubia, José Luis Martínez
A Data-Driven Probabilistic CTU Splitting Algorithm for Fast H.264/HEVC Video Transcoding. DCC 2015: 449 - [c41]Juan Ignacio Alonso-Barba, Luis de la Ossa
Ant Colony and Surrogate Tree-Structured Models for Orderings-Based Bayesian Network Learning. GECCO 2015: 543-550 - [c40]Jacinto Arias, José A. Gámez, José Miguel Puerta:
Scalable Learning of k-dependence Bayesian Classifiers under MapReduce. TrustCom/BigDataSE/ISPA (2) 2015: 25-32 - [e1]José Miguel Puerta, José A. Gámez
Advances in Artificial Intelligence - 16th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2015, Albacete, Spain, November 9-12, 2015, Proceedings. Lecture Notes in Computer Science 9422, Springer 2015, ISBN 978-3-319-24597-3 [contents] - 2014
- [j19]Pablo Bermejo
Speeding up incremental wrapper feature subset selection with Naive Bayes classifier. Knowl. Based Syst. 55: 140-147 (2014) - [c39]Antonio Jesús Díaz-Honrubia, José Luis Martínez
Fast quadtree level decision algorithm for H.264/HEVC transcoder. ICIP 2014: 2497-2501 - [c38]Jacinto Arias, José A. Gámez, Thomas D. Nielsen
A Pairwise Class Interaction Framework for Multilabel Classification. Probabilistic Graphical Models 2014: 17-32 - 2013
- [j18]Juan Ignacio Alonso-Barba, Luis delaOssa
Scaling up the Greedy Equivalence Search algorithm by constraining the search space of equivalence classes. Int. J. Approx. Reason. 54(4): 429-451 (2013) - [c37]Pablo Bermejo
Single- and Multi-label Prediction of Burden on Families of Schizophrenia Patients. AIME 2013: 115-124 - [c36]Jacinto Arias, José A. Gámez
Learning more Accurate Bayesian Networks in the CHC Approach by Adjusting the Trade-Off between Efficiency and Accuracy. CAEPIA 2013: 310-320 - 2012
- [j17]Pablo Bermejo
Fast wrapper feature subset selection in high-dimensional datasets by means of filter re-ranking. Knowl. Based Syst. 25(1): 35-44 (2012) - [j16]José A. Gámez, Juan L. Mateo, José Miguel Puerta:
One iteration CHC algorithm for learning Bayesian networks: an effective and efficient algorithm for high dimensional problems. Prog. Artif. Intell. 1(4): 329-346 (2012) - [c35]Pablo Bermejo, Luis Redondo, Luis delaOssa, Daniel Rodríguez, M. Julia Flores, Carmen Urea, José A. Gámez, Jesus Martínez-Gómez, José Miguel Puerta:
Evaluation of a Thermal-Comfort Control System Using Real Data. KES 2012: 746-755 - 2011
- [j15]M. Julia Flores
Handling numeric attributes when comparing Bayesian network classifiers: does the discretization method matter? Appl. Intell. 34(3): 372-385 (2011) - [j14]José A. Gámez
Learning Bayesian networks by hill climbing: efficient methods based on progressive restriction of the neighborhood. Data Min. Knowl. Discov. 22(1-2): 106-148 (2011) - [j13]Pablo Bermejo
Improving the performance of Naive Bayes multinomial in e-mail foldering by introducing distribution-based balance of datasets. Expert Syst. Appl. 38(3): 2072-2080 (2011) - [j12]Pablo Bermejo
Improving Incremental Wrapper-Based Subset Selection via Replacement and Early Stopping. Int. J. Pattern Recognit. Artif. Intell. 25(5): 605-625 (2011) - [j11]Pablo Bermejo
A GRASP algorithm for fast hybrid (filter-wrapper) feature subset selection in high-dimensional datasets. Pattern Recognit. Lett. 32(5): 701-711 (2011) - [j10]Juan Ignacio Alonso-Barba, Luis delaOssa
Structural learning of Bayesian networks using local algorithms based on the space of orderings. Soft Comput. 15(10): 1881-1895 (2011) - [j9]María José del Jesus
On the discovery of association rules by means of evolutionary algorithms. WIREs Data Mining Knowl. Discov. 1(5): 397-415 (2011) - [c34]Pablo Bermejo
Global Feature Subset Selection on High-Dimensional Datasets Using Re-ranking-based EDAs. CAEPIA 2011: 54-63 - [c33]Javier Cózar, Luis de la Ossa
Learning Cooperative TSK-0 Fuzzy Rules Using Fast Local Search Algorithms. CAEPIA 2011: 353-362 - [c32]Juan Ignacio Alonso-Barba, Luis de la Ossa
Scaling Up the Greedy Equivalence Search Algorithm by Constraining the Search Space of Equivalence Classes. ECSQARU 2011: 194-205 - [c31]Pablo Bermejo, Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Enhancing Incremental Feature Subset Selection in High-Dimensional Databases by Adding a Backward Step. ISCIS 2011: 93-97 - [c30]Juan Ignacio Alonso-Barba, Luis delaOssa
Efficient and sound evaluation when learning Bayesian networks in the space of orderings based on local methods. ISDA 2011: 611-618 - [c29]Pablo Bermejo
A study on different backward feature selection criteria over high-dimensional databases. ISDA 2011: 1300-1305 - 2010
- [c28]Luis delaOssa
Learning cooperative linguistic fuzzy rules using fast local search algorithms. FUZZ-IEEE 2010: 1-8 - [c27]Alejandro Revuelta-Martínez, Ismael García-Varea
ISDM at ImageCLEF 2010 Fusion Task. ICPR Contests 2010: 109-118 - [c26]M. Julia Flores
Analyzing the Impact of the Discretization Method When Comparing Bayesian Classifiers. IEA/AIE (1) 2010: 570-579 - [c25]Pablo Bermejo
Improving Incremental Wrapper-Based Feature Subset Selection by Using Re-ranking. IEA/AIE (1) 2010: 580-589
2000 – 2009
- 2009
- [j8]Luis de la Ossa
Learning weighted linguistic fuzzy rules by using specifically-tailored hybrid estimation of distribution algorithms. Int. J. Approx. Reason. 50(3): 541-560 (2009) - [j7]María José del Jesus
Evolutionary and metaheuristics based data mining. Soft Comput. 13(3): 209-212 (2009) - [c24]Luis de la Ossa, José A. Gámez
Avoiding premature convergence in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation 2009: 455-462 - [c23]Pablo Bermejo, José A. Gámez
Incremental Wrapper-based subset Selection with replacement: An advantageous alternative to sequential forward selection. CIDM 2009: 367-374 - [c22]M. Julia Flores
HODE: Hidden One-Dependence Estimator. ECSQARU 2009: 481-492 - [c21]M. Julia Flores, José A. Gámez
GAODE and HAODE: two proposals based on AODE to deal with continuous variables. ICML 2009: 313-320 - [c20]Pablo Bermejo
Comparison of balancing techniques for multimedia IR over imbalanced datasets. ISCIS 2009: 674-679 - [c19]Juan Ignacio Alonso-Barba, Luis delaOssa
Structural Learning of Bayesian Networks by Using Variable Neighbourhood Search Based on the Space of Orderings. ISDA 2009: 1435-1440 - 2008
- [c18]José A. Gámez, Juan L. Mateo, José Miguel Puerta:
Improved EDNA (estimation of dependency networks algorithm) using combining function with bivariate probability distributions. GECCO 2008: 407-414 - [c17]Juan Ignacio Alonso-Barba, José A. Gámez
Gait Optimization in AIBO Robots Using an Estimation of Distribution Algorithm. HIS 2008: 150-155 - 2007
- [j6]Luis de la Ossa
Initial breeding value prediction on Manchego sheep by using rule-based systems. Expert Syst. Appl. 33(1): 96-109 (2007) - [c16]José A. Gámez, Juan L. Mateo, José Miguel Puerta:
A Fast Hill-Climbing Algorithm for Bayesian Networks Structure Learning. ECSQARU 2007: 585-597 - [c15]José A. Gámez, Juan L. Mateo, José Miguel Puerta:
Learning Bayesian Classifiers from Dependency Network Classifiers. ICANNGA (1) 2007: 806-813 - [c14]Pablo Bermejo, José A. Gámez, José Miguel Puerta:
Attribute Construction for E-Mail Foldering by Using Wrappered Forward Greedy Search. ICEIS (2) 2007: 247-252 - [c13]José A. Gámez, Juan L. Mateo, José Miguel Puerta:
EDNA: Estimation of Dependency Networks Algorithm. IWINAC (1) 2007: 427-436 - [c12]José A. Gámez, Juan L. Mateo, José Miguel Puerta:
Improving Revisitation Browsers Capability by Using a Dynamic Bookmarks Personal Toolbar. WISE 2007: 643-652 - 2006
- [j5]M. Julia Flores, José A. Gámez, Juan L. Mateo, José Miguel Puerta:
Seleccion genetica para la mejora de la raza ovina manchega mediante tecnicas de Mineria de Datos. Inteligencia Artif. 10(29): 69-77 (2006) - [j4]Luis de la Ossa
Initial approaches to the application of islands-based parallel EDAs in continuous domains. J. Parallel Distributed Comput. 66(8): 991-1001 (2006) - [c11]Luis delaOssa, José A. Gámez, José Miguel Puerta:
Learning weighted linguistic fuzzy rules with estimation of distribution algorithms. IEEE Congress on Evolutionary Computation 2006: 900-907 - [c10]Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Improvement in the Performance of Island Based Genetic Algorithms Through Path Relinking. Hybrid Metaheuristics 2006: 42-56 - [c9]José A. Gámez, Juan L. Mateo, José Miguel Puerta:
Dependency networks based classifiers: learning models by using independence. Probabilistic Graphical Models 2006: 115-122 - [p1]M. Julia Flores, José A. Gámez, José Miguel Puerta:
Learning Linguistic Fuzzy Rules by Using Estimation of Distribution Algorithms as the Search Engine in the COR Methodology. Towards a New Evolutionary Computation 2006: 259-280 - 2005
- [c8]Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Improving model combination through local search in parallel univariate EDAs. Congress on Evolutionary Computation 2005: 1426-1433 - [c7]José A. Gámez, José Miguel Puerta:
Constrained Score+(Local)Search Methods for Learning Bayesian Networks. ECSQARU 2005: 161-173 - [c6]Luis de la Ossa
Initial Approaches to the Application of Islands-Based Parallel EDAs in Continuous Domains. ICPP Workshops 2005: 580-587 - 2004
- [c5]Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Migration of Probability Models Instead of Individuals: An Alternative When Applying the Island Model to EDAs. PPSN 2004: 242-252 - 2003
- [j3]Luis M. de Campos
An iterated local search algorithm for learning Bayesian networks with restarts based on conditional independence tests. Int. J. Intell. Syst. 18(2): 221-235 (2003) - [c4]Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Heuristic Based Sampling in Estimation of Distribution Algorithms: An Initial Approach. CAEPIA 2003: 384-393 - 2002
- [j2]Luis M. de Campos
Ant colony optimization for learning Bayesian networks. Int. J. Approx. Reason. 31(3): 291-311 (2002) - [j1]José A. Gámez
Searching for the best elimination sequence in Bayesian networks by using ant colony optimization. Pattern Recognit. Lett. 23(1-3): 261-277 (2002) - [c3]Luis M. de Campos
Local Search Methods for Learning Bayesian Networks Using a Modified Neighborhood in the Space of DAGs. IBERAMIA 2002: 182-192 - [c2]Luis M. de Campos, José A. Gámez, José Miguel Puerta:
Graphical Models to Causal Discovery from Data. Probabilistic Graphical Models 2002 - 2001
- [c1]Luis M. de Campos
Stochastic Local Algorithms for Learning Belief Networks: Searching in the Space of the Orderings. ECSQARU 2001: 228-239
Coauthor Index
M. Julia Flores
aka: María Julia Flores Gallego
aka: María Julia Flores Gallego
José A. Gámez 0001
aka: José Antonio Gámez
aka: José Antonio Gámez
[j41] [j40] [c55] [c54] [c53] [c52] [i3] [i2] [c51] [c50] [i1] [j36] [j34] [c49] [c48] [c47] [j33] [j32] [c46] [j31] [j30] [j29] [j28] [j26] [c45] [j24] [j23] [j22] [c43] [j20] [c42] [c41] [c40] [e1] [j19] [c39] [c38] [j18] [c37] [c36] [j17] [j16] [c35] [j15] [j14] [j13] [j12] [j11] [j9] [c32] [c31] [c29] [c28] [c26] [c25] [j8] [j7] [c24] [c23] [c22] [c21] [c20] [c18] [c17] [j6] [c16] [c15] [c14] [c13] [c12] [j5] [j4] [c11] [c10] [c9] [p1] [c8] [c7] [c6] [c5] [c4] [j2] [j1] [c2]
Luis de la Ossa
aka: Luis delaOssa
aka: Luis delaOssa
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