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ORCIDJosé A. Gámez 0001
José Antonio Gámez
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- affiliation: University of Castilla-La Mancha, Spain
Other persons with the same name
- José A. Gámez 0002 — RWTH Aachen University, Germany
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2020 – today
- 2024
[j78]Enrique González Rodrigo, Juan C. Alfaro, Juan A. Aledo, José A. Gámez
:
Efficient ensembles of distance-based label ranking trees. Expert Syst. J. Knowl. Eng. 41(4) (2024)- [j77]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) - [j76]Jorge D. Laborda, Pablo Torrijos, José Miguel Puerta, José A. Gámez:
Parallel structural learning of Bayesian networks: Iterative divide and conquer algorithm based on structural fusion. Knowl. Based Syst. 296: 111840 (2024) - [j75]Enrique González Rodrigo, Juan C. Alfaro, Juan A. Aledo, José A. Gámez:
Label ranking oblique trees. Knowl. Based Syst. 296: 111882 (2024) - [c82]Pablo Torrijos, José A. Gámez, José Miguel Puerta:
Structural Fusion of Bayesian Networks with Limited Treewidth Using Genetic Algorithms. CEC 2024: 1-8 - [c81]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 - [c80]Guillermo Fernández, Riccardo Guidotti, Fosca Giannotti, Mattia Setzu, Juan A. Aledo, José A. Gámez, José Miguel Puerta:
FLocalX - Local to Global Fuzzy Explanations for Black Box Classifiers. IDA (2) 2024: 197-209 - [c79]Pablo Torrijos, Juan C. Alfaro, José A. Gámez, José Miguel Puerta:
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) - 2023
- [j74]Víctor Pérez-Piqueras, Pablo Bermejo, José A. Gámez:
FEDA-NRP: A fixed-structure multivariate estimation of distribution algorithm to solve the multi-objective Next Release Problem with requirements interactions. Eng. Appl. Artif. Intell. 124: 106555 (2023) - [j73]Juan C. Alfaro, Juan A. Aledo, José A. Gámez:
Multi-dimensional Bayesian network classifiers for partial label ranking. Int. J. Approx. Reason. 160: 108950 (2023) - [j72]Juan C. Alfaro, Juan A. Aledo, José A. Gámez:
Pairwise learning for the partial label ranking problem. Pattern Recognit. 140: 109590 (2023) - [c78]Pablo Torrijos, José A. Gámez, José Miguel Puerta:
MiniAnDE: A Reduced AnDE Ensemble to Deal with Microarray Data. EANN 2023: 131-143 - [c77]Jorge D. Laborda, Pablo Torrijos, José Miguel Puerta, José A. Gámez:
A Ring-Based Distributed Algorithm for Learning High-Dimensional Bayesian Networks. ECSQARU 2023: 123-135 - [c76]Víctor Pérez-Piqueras, Pablo Bermejo, José A. Gámez:
Hybrid Multi-Objective Relinked GRASP for the constrained Next Release Problem. TrustCom 2023: 2349-2356 - [i2]Pablo Torrijos, José A. Gámez, José Miguel Puerta:
MiniAnDE: a reduced AnDE ensemble to deal with microarray data. CoRR abs/2311.12879 (2023) - 2022
- [j71]Guillermo Fernández, Juan A. Aledo, José Antonio Gámez, José Miguel Puerta:
Factual and Counterfactual Explanations in Fuzzy Classification Trees. IEEE Trans. Fuzzy Syst. 30(12): 5484-5495 (2022) - [c75]Víctor Pérez-Piqueras, Pablo Bermejo López, José A. Gámez:
GRASP-Based Hybrid Search to Solve the Multi-objective Requirements Selection Problem. OLA 2022: 189-200 - [c74]Juan C. Alfaro, Juan A. Aledo, José A. Gámez:
Integrating Bayesian network classifiers to deal with the partial label ranking problem. PGM 2022: 337-348 - [c73]Víctor Pérez-Piqueras, Pablo Bermejo López, José A. Gámez:
Estimation of Distribution Algorithms Applied to the Next Release Problem. SOCO 2022: 98-108 - 2021
- [j70]Annalisa Appice, Sergio Escalera, José A. Gámez, Heike Trautmann:
Introduction to the special issue of the ECML PKDD 2021 journal track. Data Min. Knowl. Discov. 35(6): 2540-2541 (2021) - [j69]Enrique González Rodrigo, Juan C. Alfaro, Juan A. Aledo, José A. Gámez:
Mixture-Based Probabilistic Graphical Models for the Label Ranking Problem. Entropy 23(4): 420 (2021) - [j68]Juan C. Alfaro, Juan A. Aledo, José A. Gámez:
Learning decision trees for the partial label ranking problem. Int. J. Intell. Syst. 36(2): 890-918 (2021) - [j67]José Miguel Puerta, Juan A. Aledo, José A. Gámez, Jorge D. Laborda:
Efficient and accurate structural fusion of Bayesian networks. Inf. Fusion 66: 155-169 (2021) - [j66]Juan A. Aledo, José A. Gámez, Alejandro Rosete:
A highly scalable algorithm for weak rankings aggregation. Inf. Sci. 570: 144-171 (2021) - [j65]Annalisa Appice, Sergio Escalera, José A. Gámez, Heike Trautmann:
Introduction to the special issue of the ECML PKDD 2021 journal track. Mach. Learn. 110(10): 2991-2992 (2021) - [c72]Ricardo Montañana, José A. Gámez, José Miguel Puerta:
STree: A Single Multi-class Oblique Decision Tree Based on Support Vector Machines. CAEPIA 2021: 54-64 - [c71]Juan C. Alfaro, Juan A. Aledo, José A. Gámez:
Mixture-Based Probabilistic Graphical Models for the Partial Label Ranking Problem. IDEAL 2021: 277-288 - [c70]Alejandro Zornoza Martínez, Jesus Martínez-Gómez, José A. Gámez:
A Data-Driven Approach for Components Useful Life Estimation in Wind Turbines. SOCO 2021: 37-47 - 2020
- [j64]F. Javier Ramírez, Juan A. Aledo, José A. Gámez, Duc Truong Pham:
Economic modelling of robotic disassembly in end-of-life product recovery for remanufacturing. Comput. Ind. Eng. 142: 106339 (2020) - [c69]Juan C. Alfaro, Juan A. Aledo, José A. Gámez:
Averaging-Based Ensemble Methods for the Partial Label Ranking Problem. HAIS 2020: 410-423
2010 – 2019
- 2019
- [j63]Juan A. Aledo, José A. Gámez, David Molina:
Approaching the rank aggregation problem by local search-based metaheuristics. J. Comput. Appl. Math. 354: 445-456 (2019) - [j62]Enrique González Rodrigo, Juan A. Aledo, José A. Gámez:
spark-crowd: A Spark Package for Learning from Crowdsourced Big Data. J. Mach. Learn. Res. 20: 19:1-19:5 (2019) - [j61]Enrique González Rodrigo, Juan A. Aledo, José A. Gámez:
Scaling up the learning-from-crowds GLAD algorithm using instance-difficulty clustering. Prog. Artif. Intell. 8(3): 389-399 (2019) - [j60]Javier Cózar, Alberto Fernández, Francisco Herrera, José A. Gámez:
A Metahierarchical Rule Decision System to Design Robust Fuzzy Classifiers Based on Data Complexity. IEEE Trans. Fuzzy Syst. 27(4): 701-715 (2019) - [j59]Enrique González Rodrigo, Juan A. Aledo, José A. Gámez:
Machine learning from crowds: A systematic review of its applications. WIREs Data Mining Knowl. Discov. 9(2) (2019) - [c68]Juan Carlos Alfaro Jiménez, Enrique González Rodrigo, Juan A. Aledo, José Antonio Gámez:
A Probabilistic Graphical Model-Based Approach for the Label Ranking Problem. ECSQARU 2019: 351-362 - [c67]José Miguel Puerta, Juan A. Aledo, José Antonio Gámez, Jorge D. Laborda:
Structural Fusion/Aggregation of Bayesian Networks via Greedy Equivalence Search Learning Algorithm. ECSQARU 2019: 432-443 - [c66]Luis de la Ossa, Pablo Bermejo, Juan A. Aledo, José A. Gámez, José Miguel Puerta, Cristina Romero-González, Jacinto Arias, Javier Cózar, Enrique González Rodrigo, Juan Ignacio Alonso-Barba, Jesus Martínez-Gómez:
CiDAEN: An Online Data Science Course. HELMeTO 2019: 113-124 - 2018
- [j58]Juan Ignacio Alonso-Barba, Luis de la Ossa, José A. Gámez, José Miguel Puerta:
On the use of local search heuristics to improve GES-based Bayesian network learning. Appl. Soft Comput. 64: 366-376 (2018) - [j57]Juan A. Aledo, José A. Gámez, Alejandro Rosete:
Approaching rank aggregation problems by using evolution strategies: The case of the optimal bucket order problem. Eur. J. Oper. Res. 270(3): 982-998 (2018) - [j56]Pablo Bermejo, José A. Gámez, José Miguel Puerta:
Adapting the CMIM algorithm for multilabel feature selection. A comparison with existing methods. Expert Syst. J. Knowl. Eng. 35(1) (2018) - [j55]Javier Cózar, Luis delaOssa, José A. Gámez:
Learning compact zero-order TSK fuzzy rule-based systems for high-dimensional problems using an Apriori + local search approach. Inf. Sci. 433-434: 1-16 (2018) - [j54]Juan A. Aledo, José A. Gámez, David Molina, Alejandro Rosete:
Consensus-based journal rankings: A complementary tool for bibliometric evaluation. J. Assoc. Inf. Sci. Technol. 69(7): 936-948 (2018) - [j53]Javier Cózar, Francesco Marcelloni, José A. Gámez, Luis de la Ossa:
Building efficient fuzzy regression trees for large scale and high dimensional problems. J. Big Data 5: 49 (2018) - [c65]Enrique González Rodrigo, Juan A. Aledo, José A. Gámez:
CGLAD: Using GLAD in Crowdsourced Large Datasets. IDEAL (1) 2018: 783-791 - [c64]Jacinto Arias, José A. Gámez, José Miguel Puerta:
Bayesian Network Classifiers Under the Ensemble Perspective. PGM 2018: 1-12 - 2017
- [j52]Juan A. Aledo, José A. Gámez, Alejandro Rosete:
Partial evaluation in Rank Aggregation Problems. Comput. Oper. Res. 78: 299-304 (2017) - [j51]Juan A. Aledo, José A. Gámez, Alejandro Rosete:
Utopia in the solution of the Bucket Order Problem. Decis. Support Syst. 97: 69-80 (2017) - [j50]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) - [j49]José A. Gámez, Francisco Herrera, José Miguel Puerta:
Guest Editorial: Recent Trends in Intelligent Systems. Int. J. Intell. Syst. 32(2): 107-108 (2017) - [j48]Juan A. Aledo, José A. Gámez, David Molina:
Tackling the supervised label ranking problem by bagging weak learners. Inf. Fusion 35: 38-50 (2017) - [j47]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) - [j46]Jacinto Arias, José A. Gámez, José Miguel Puerta:
Learning distributed discrete Bayesian Network Classifiers under MapReduce with Apache Spark. Knowl. Based Syst. 117: 16-26 (2017) - [j45]Antonio Jesús Díaz-Honrubia, Johan De Praeter, Glenn Van Wallendael, José Luis Martínez, Pedro Cuenca, José Miguel Puerta, José A. Gámez:
CTU splitting algorithm for H.264/AVC and HEVC simultaneous encoding. J. Supercomput. 73(1): 190-202 (2017) - [c63]Javier Cózar, Luis de la Ossa, José A. Gámez:
Generation of first-order TSK rules based on the apriori + search approach. CEC 2017: 1675-1682 - [c62]Rafael Rivera-López, Juana Canul-Reich, José A. Gámez, José Miguel Puerta:
OC1-DE: A Differential Evolution Based Approach for Inducing Oblique Decision Trees. ICAISC (1) 2017: 427-438 - 2016
- [j44]Juan A. Aledo, José A. Gámez, David Molina:
Using extension sets to aggregate partial rankings in a flexible setting. Appl. Math. Comput. 290: 208-223 (2016) - [j43]Juan A. Aledo, José A. Gámez, David Molina:
Using metaheuristic algorithms for parameter estimation in generalized Mallows models. Appl. Soft Comput. 38: 308-320 (2016) - [j42]Jacinto Arias, Jesus Martínez-Gómez, José A. Gámez, Alba Garcia Seco de Herrera, Henning Müller:
Medical image modality classification using discrete Bayesian networks. Comput. Vis. Image Underst. 151: 61-71 (2016) - [j41]Jacinto Arias, José A. Gámez, Thomas D. Nielsen, José Miguel Puerta:
A scalable pairwise class interaction framework for multidimensional classification. Int. J. Approx. Reason. 68: 194-210 (2016) - [j40]Antonio Jesús Díaz-Honrubia, Gabriel Cebrián-Márquez, José Luis Martínez, Pedro Cuenca, José Miguel Puerta, José Antonio Gámez:
Low-complexity heterogeneous architecture for H.264/HEVC video transcoding. J. Real Time Image Process. 12(2): 311-327 (2016) - [j39]Gonzalo Vergara, Juan Ignacio Alonso-Barba, Emilio Soria-Olivas, José A. Gámez, Manuel Domínguez:
Random extreme learning machines to predict electric load in buildings. Prog. Artif. Intell. 5(2): 129-135 (2016) - [j38]Antonio Jesús Díaz-Honrubia, José Luis Martínez, Pedro Cuenca, José Antonio Gámez, José Miguel Puerta:
Adaptive Fast Quadtree Level Decision Algorithm for H.264 to HEVC Video Transcoding. IEEE Trans. Circuits Syst. Video Technol. 26(1): 154-168 (2016) - [c61]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 - [c60]Juan A. Aledo, José A. Gámez, David Molina, Alejandro Rosete:
FSS-OBOP: Feature subset selection guided by a bucket order consensus ranking. SSCI 2016: 1-8 - [e4]Oscar Luaces, José A. Gámez, Edurne Barrenechea, Alicia Troncoso, Mikel Galar, Héctor Quintián, Emilio Corchado:
Advances in Artificial Intelligence - 17th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2016, Salamanca, Spain, September 14-16, 2016. Proceedings. Lecture Notes in Computer Science 9868, Springer 2016, ISBN 978-3-319-44635-6 [contents] - 2015
- [j37]Jacinto Arias, José A. Gámez, José Miguel Puerta:
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) - [c59]Antonio Jesús Díaz-Honrubia, José Luis Martínez, Pedro Cuenca, José Antonio Gámez, José Miguel Puerta:
A Data-Driven Probabilistic CTU Splitting Algorithm for Fast H.264/HEVC Video Transcoding. DCC 2015: 449 - [c58]Javier Cózar, Gonzalo Vergara, José A. Gámez, Emilio Soria-Olivas:
Comparing TSK-1 FRBS against SVR for electrical power prediction in buildings. IFSA-EUSFLAT 2015 - [c57]Juan Ignacio Alonso-Barba, Luis de la Ossa, Olivier Regnier-Coudert, John A. W. McCall, José A. Gámez, José Miguel Puerta:
Ant Colony and Surrogate Tree-Structured Models for Orderings-Based Bayesian Network Learning. GECCO 2015: 543-550 - [c56]M. Julia Flores, José A. Gámez:
Impact on Bayesian Networks Classifiers When Learning from Imbalanced Datasets. ICAART (2) 2015: 382-389 - [c55]Gonzalo Vergara, Javier Cózar, Cristina Romero-González, José A. Gámez, Emilio Soria-Olivas:
Comparing ELM Against MLP for Electrical Power Prediction in Buildings. IWINAC (2) 2015: 409-418 - [c54]Jacinto Arias, José A. Gámez, José Miguel Puerta:
Scalable Learning of k-dependence Bayesian Classifiers under MapReduce. TrustCom/BigDataSE/ISPA (2) 2015: 25-32 - [e3]José Miguel Puerta, José A. Gámez, Bernabé Dorronsoro, Edurne Barrenechea, Alicia Troncoso, Bruno Baruque, Mikel Galar:
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
- [j36]Javier Cózar, Luis de la Ossa, José A. Gámez:
Learning TSK-0 linguistic fuzzy rules by means of local search algorithms. Appl. Soft Comput. 21: 57-71 (2014) - [j35]Jens Dalgaard Nielsen, Antonio Salmerón, José A. Gámez:
A tool based on Bayesian networks for supporting geneticists in plant improvement by controlled pollination. Int. J. Approx. Reason. 55(1): 74-83 (2014) - [j34]M. Julia Flores, José A. Gámez, Ana M. Martínez:
Domains of competence of the semi-naive Bayesian network classifiers. Inf. Sci. 260: 120-148 (2014) - [j33]Pablo Bermejo, José A. Gámez, José Miguel Puerta:
Speeding up incremental wrapper feature subset selection with Naive Bayes classifier. Knowl. Based Syst. 55: 140-147 (2014) - [j32]Antonio Fernández, José A. Gámez, Rafael Rumí, Antonio Salmerón:
Data clustering using hidden variables in hybrid Bayesian networks. Prog. Artif. Intell. 2(2-3): 141-152 (2014) - [c53]Antonio Jesús Díaz-Honrubia, José Luis Martínez, José Miguel Puerta, José A. Gámez, Jan De Cock, Pedro Cuenca:
Fast quadtree level decision algorithm for H.264/HEVC transcoder. ICIP 2014: 2497-2501 - [c52]Jacinto Arias, José A. Gámez, Thomas D. Nielsen, José Miguel Puerta:
A Pairwise Class Interaction Framework for Multilabel Classification. Probabilistic Graphical Models 2014: 17-32 - [c51]Javier Cózar, Luis de la Ossa, José A. Gámez:
TSK-0 Fuzzy Rule-Based Systems for High-Dimensional Problems Using the Apriori Principle for Rule Generation. RSCTC 2014: 270-279 - 2013
- [j31]Juan A. Aledo, José A. Gámez, David Molina:
Tackling the rank aggregation problem with evolutionary algorithms. Appl. Math. Comput. 222: 632-644 (2013) - [j30]Juan Ignacio Alonso-Barba, Luis delaOssa, José A. Gámez, José Miguel Puerta:
Scaling up the Greedy Equivalence Search algorithm by constraining the search space of equivalence classes. Int. J. Approx. Reason. 54(4): 429-451 (2013) - [j29]Juan A. Villar, Francisco J. Andujar, José L. Sánchez, Francisco J. Alfaro, José A. Gámez, José Duato:
Obtaining the optimal configuration of high-radix Combined switches. J. Parallel Distributed Comput. 73(9): 1239-1250 (2013) - [c50]Pablo Bermejo, Marta Lucas, José A. Rodríguez-Montes, Pedro J. Tárraga, Javier Lucas, José A. Gámez, José Miguel Puerta:
Single- and Multi-label Prediction of Burden on Families of Schizophrenia Patients. AIME 2013: 115-124 - [c49]Jacinto Arias, José A. Gámez, José Miguel Puerta:
Learning more Accurate Bayesian Networks in the CHC Approach by Adjusting the Trade-Off between Efficiency and Accuracy. CAEPIA 2013: 310-320 - [c48]Juan A. Aledo, José A. Gámez, David Molina:
Computing the Consensus Permutation in Mallows Distribution by Using Genetic Algorithms. IEA/AIE 2013: 102-111 - 2012
- [j28]Jens Dalgaard Nielsen, José A. Gámez, Antonio Salmerón:
Modelling and inference with Conditional Gaussian Probabilistic Decision Graphs. Int. J. Approx. Reason. 53(7): 929-945 (2012) - [j27]Pablo Bermejo, Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Fast wrapper feature subset selection in high-dimensional datasets by means of filter re-ranking. Knowl. Based Syst. 25(1): 35-44 (2012) - [j26]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) - [c47]Ana M. Martínez, Geoffrey I. Webb, M. Julia Flores, José A. Gámez:
Non-Disjoint Discretization for Aggregating One-Dependence Estimator Classifiers. HAIS (2) 2012: 151-162 - [c46]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 - [i1]M. Julia Flores, José A. Gámez, Kristian G. Olesen:
Incremental Compilation of Bayesian networks. CoRR abs/1212.2456 (2012) - 2011
- [j25]M. Julia Flores, José A. Gámez, Ana M. Martínez, José Miguel Puerta:
Handling numeric attributes when comparing Bayesian network classifiers: does the discretization method matter? Appl. Intell. 34(3): 372-385 (2011) - [j24]Oscar Cordón, Antonio Fernández-Caballero, José A. Gámez, Frank Hoffmann:
The impact of soft computing for the progress of artificial intelligence. Appl. Soft Comput. 11(2): 1491-1492 (2011) - [j23]José A. Gámez, Juan L. Mateo, José Miguel Puerta:
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) - [j22]Pablo Bermejo, José A. Gámez, José Miguel Puerta:
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) - [j21]Pablo Bermejo, José A. Gámez, José Miguel Puerta:
Improving Incremental Wrapper-Based Subset Selection via Replacement and Early Stopping. Int. J. Pattern Recognit. Artif. Intell. 25(5): 605-625 (2011) - [j20]M. Julia Flores, José A. Gámez, Kristian G. Olesen:
Incremental Compilation of Bayesian Networks Based on Maximal Prime Subgraphs. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 19(2): 155-191 (2011) - [j19]Pablo Bermejo, José A. Gámez, José Miguel Puerta:
A GRASP algorithm for fast hybrid (filter-wrapper) feature subset selection in high-dimensional datasets. Pattern Recognit. Lett. 32(5): 701-711 (2011) - [j18]María José del Jesus, José A. Gámez, Pedro González, José Miguel Puerta:
On the discovery of association rules by means of evolutionary algorithms. WIREs Data Mining Knowl. Discov. 1(5): 397-415 (2011) - [c45]Juan Ignacio Alonso-Barba, Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Scaling Up the Greedy Equivalence Search Algorithm by Constraining the Search Space of Equivalence Classes. ECSQARU 2011: 194-205 - [c44]Arcadio Rubio, José Antonio Gámez:
Flexible learning of k-dependence Bayesian network classifiers. GECCO 2011: 1219-1226 - [c43]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 - [c42]Javier Cózar, Luis delaOssa, José A. Gámez:
Learning heterogeneus cooperative linguistic fuzzy rules using local search: Enhancing the COR search space. ISDA 2011: 475-480 - [c41]M. Julia Flores, José A. Gámez, Ana M. Martínez, Antonio Salmerón:
Mixture of truncated exponentials in supervised classification: Case study for the naive bayes and averaged one-dependence estimators classifiers. ISDA 2011: 593-598 - [c40]Pablo Bermejo, Luis de la Ossa, José A. Gámez, José Miguel Puerta:
A study on different backward feature selection criteria over high-dimensional databases. ISDA 2011: 1300-1305 - [e2]José Antonio Lozano, José A. Gámez, José A. Moreno:
Advances in Artificial Intelligence - 14th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2011, La Laguna, Spain, November 7-11, 2011. Proceedings. Lecture Notes in Computer Science 7023, Springer 2011, ISBN 978-3-642-25273-0 [contents] - 2010
- [c39]Jesus Martínez-Gómez, José A. Gámez, Ismael García-Varea:
Comparing Cellular and Panmictic Genetic Algorithms for Real-Time Object Detection. EvoApplications (1) 2010: 261-271 - [c38]Luis delaOssa, José A. Gámez, José Miguel Puerta:
Learning cooperative linguistic fuzzy rules using fast local search algorithms. FUZZ-IEEE 2010: 1-8 - [c37]Jesus Martínez-Gómez, Alejandro Jiménez-Picazo, José A. Gámez, Ismael García-Varea:
Combining Image Invariant Features and Clustering Techniques for Visual Place Classification. ICPR Contests 2010: 200-209 - [c36]M. Julia Flores, José A. Gámez, Ana M. Martínez, José Miguel Puerta:
Analyzing the Impact of the Discretization Method When Comparing Bayesian Classifiers. IEA/AIE (1) 2010: 570-579 - [c35]Pablo Bermejo, José A. Gámez, José Miguel Puerta:
Improving Incremental Wrapper-Based Feature Subset Selection by Using Re-ranking. IEA/AIE (1) 2010: 580-589
2000 – 2009
- 2009
- [j17]Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Learning weighted linguistic fuzzy rules by using specifically-tailored hybrid estimation of distribution algorithms. Int. J. Approx. Reason. 50(3): 541-560 (2009) - [j16]María José del Jesus, José A. Gámez, José Miguel Puerta:
Evolutionary and metaheuristics based data mining. Soft Comput. 13(3): 209-212 (2009) - [c34]Luis de la Ossa, José A. Gámez, Juan L. Mateo, José Miguel Puerta:
Avoiding premature convergence in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation 2009: 455-462 - [c33]Pablo Bermejo, José A. Gámez, José Miguel Puerta:
Incremental Wrapper-based subset Selection with replacement: An advantageous alternative to sequential forward selection. CIDM 2009: 367-374 - [c32]M. Julia Flores, José A. Gámez, Jens Dalgaard Nielsen:
The PDG-Mixture Model for Clustering. DaWaK 2009: 378-389 - [c31]M. Julia Flores, José A. Gámez, Ana M. Martínez, José Miguel Puerta:
HODE: Hidden One-Dependence Estimator. ECSQARU 2009: 481-492 - [c30]M. Julia Flores, José A. Gámez, Ana M. Martínez, José Miguel Puerta:
GAODE and HAODE: two proposals based on AODE to deal with continuous variables. ICML 2009: 313-320 - [c29]Pablo Bermejo, Frank Hopfgartner, José A. Gámez, José Miguel Puerta, Joemon M. Jose:
Comparison of balancing techniques for multimedia IR over imbalanced datasets. ISCIS 2009: 674-679 - [c28]Jesus Martínez-Gómez, José A. Gámez, Ismael García-Varea, Vicente Matellán:
Using Genetic Algorithms for Real-Time Object Detection. RoboCup 2009: 215-227 - 2008
- [j15]Luis Rodríguez, Ismael García-Varea, José A. Gámez:
On the application of different evolutionary algorithms to the alignment problem in statistical machine translation. Neurocomputing 71(4-6): 755-765 (2008) - [j14]Gerardo Fernández-Escribano, Jens Bialkowski, José A. Gámez, Hari Kalva, Pedro Cuenca, Luis Orozco-Barbosa, André Kaup:
Low-Complexity Heterogeneous Video Transcoding Using Data Mining. IEEE Trans. Multim. 10(2): 286-299 (2008) - [c27]Luis delaOssa, José A. Gámez, Verónica López:
Improvement of a car racing controller by means of Ant Colony Optimization algorithms. CIG 2008: 365-371 - [c26]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 - [c25]Juan Ignacio Alonso-Barba, José A. Gámez, José Miguel Puerta, Ismael García-Varea:
Gait Optimization in AIBO Robots Using an Estimation of Distribution Algorithm. HIS 2008: 150-155 - [c24]José A. Gámez, Ismael García-Varea, Jesus Martínez-Gómez:
An improved Markov-based localization approach by using image quality evaluation. ICARCV 2008: 1236-1241 - [p3]M. Julia Flores, José A. Gámez, Serafín Moral:
Use of Explanation Treesto Describe the State Space of a Probabilistic-Based Abduction Problem. Innovations in Bayesian Networks 2008: 251-280 - 2007
- [j13]Luis de la Ossa, M. Julia Flores, José A. Gámez, Juan L. Mateo, José Miguel Puerta:
Initial breeding value prediction on Manchego sheep by using rule-based systems. Expert Syst. Appl. 33(1): 96-109 (2007) - [c23]José A. Gámez, Juan L. Mateo, José Miguel Puerta:
A Fast Hill-Climbing Algorithm for Bayesian Networks Structure Learning. ECSQARU 2007: 585-597 - [c22]José A. Gámez, Juan L. Mateo, José Miguel Puerta:
Learning Bayesian Classifiers from Dependency Network Classifiers. ICANNGA (1) 2007: 806-813 - [c21]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 - [c20]José A. Gámez, Juan L. Mateo, José Miguel Puerta:
EDNA: Estimation of Dependency Networks Algorithm. IWINAC (1) 2007: 427-436 - [c19]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
- [j12]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) - [j11]Peter J. F. Lucas, José A. Gámez, Antonio Salmerón:
Special issue on PGM'04: Second European workshop on probabilistic graphical models 2004. Int. J. Approx. Reason. 42(1-2): 1-3 (2006) - [j10]Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Initial approaches to the application of islands-based parallel EDAs in continuous domains. J. Parallel Distributed Comput. 66(8): 991-1001 (2006) - [c18]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 - [c17]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 - [c16]M. Julia Flores, José A. Gámez, Serafín Moral:
The Independency tree model: a new approach for clustering and factorisation. Probabilistic Graphical Models 2006: 83-90 - [c15]José A. Gámez, Juan L. Mateo, José Miguel Puerta:
Dependency networks based classifiers: learning models by using independence. Probabilistic Graphical Models 2006: 115-122 - [c14]José A. Gámez, Rafael Rumí, Antonio Salmerón:
Unsupervised naive Bayes for data clustering with mixtures of truncated exponentials. Probabilistic Graphical Models 2006: 123-130 - [c13]Luis Rodríguez, Ismael García-Varea, José A. Gámez:
Searching for alignments in SMT. A novel approach based on an Estimation of Distribution Algorithm. WMT@HLT-NAACL 2006: 47-54 - [p2]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
- [c12]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 - [c11]M. Julia Flores, José A. Gámez, Serafín Moral:
Abductive Inference in Bayesian Networks: Finding a Partition of the Explanation Space. ECSQARU 2005: 63-75 - [c10]José A. Gámez, José Miguel Puerta:
Constrained Score+(Local)Search Methods for Learning Bayesian Networks. ECSQARU 2005: 161-173 - [c9]Luis de la Ossa, José A. Gámez, José Miguel Puerta:
Initial Approaches to the Application of Islands-Based Parallel EDAs in Continuous Domains. ICPP Workshops 2005: 580-587 - [c8]M. Julia Flores, José A. Gámez:
Breeding Value Classification in Manchego Sheep: A Study of Attribute Selection and Construction. KES (2) 2005: 1338-1346 - 2004
- [c7]J. E. Villalobos, José L. Sánchez, José A. Gámez, José Carlos Sancho, Antonio Robles:
A Methodology to Evaluate the Effectiveness of Traffic Balancing Algorithms. Euro-Par 2004: 891-899 - [c6]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
- [j9]José A. Gámez, Antonio Salmerón:
Probabilistic graphical models. Int. J. Intell. Syst. 18(2): 149-151 (2003) - [j8]M. Julia Flores, José A. Gámez:
Triangulation of Bayesian networks by retriangulation. Int. J. Intell. Syst. 18(2): 153-164 (2003) - [c5]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 - [c4]Luis M. de Campos, José A. Gámez, Serafín Moral:
Partial Abductive Inference in Bayesian Networks By Using Probability Trees. ICEIS (2) 2003: 83-91 - [c3]M. Julia Flores, José A. Gámez, Kristian G. Olesen:
Incremental compilation of Bayesian networks. UAI 2003: 233-240 - 2002
- [j7]Luis M. de Campos, Juan M. Fernández-Luna, José A. Gámez, José Miguel Puerta:
Ant colony optimization for learning Bayesian networks. Int. J. Approx. Reason. 31(3): 291-311 (2002) - [j6]José A. Gámez, José Miguel Puerta:
Searching for the best elimination sequence in Bayesian networks by using ant colony optimization. Pattern Recognit. Lett. 23(1-3): 261-277 (2002) - [j5]Luis M. de Campos, José A. Gámez, Serafín Moral:
Partial abductive inference in Bayesian belief networks - an evolutionary computation approach by using problem-specific genetic operators. IEEE Trans. Evol. Comput. 6(2): 105-131 (2002) - [c2]M. Julia Flores, José A. Gámez:
Applicability of Estimation of Distribution Algorithms to the Fuzzy Rule Learning Problem: A Preliminary Study. ICEIS 2002: 350-357 - [c1]Luis M. de Campos, José A. Gámez, José Miguel Puerta:
Graphical Models to Causal Discovery from Data. Probabilistic Graphical Models 2002 - [p1]L. M. Campos, José A. Gámez, Pedro Larrañaga, Serafín Moral, Txomin Romero:
Partial Abductive Inference in Bayesian Networks: An Empirical Comparison Between GAs and EDAs. Estimation of Distribution Algorithms 2002: 323-341 - [e1]José A. Gámez, Antonio Salmerón:
First European Workshop on Probabilistic Graphical Models, 6-8 November - 2002 - Cuenca (Spain), Electronic Proceedings. 2002 [contents] - 2001
- [j4]Luis M. de Campos, José A. Gámez, Serafín Moral:
Accelerating chromosome evaluation for partial abductive inference in Bayesian networks by means of explanation set absorption. Int. J. Approx. Reason. 27(2): 121-142 (2001) - [j3]Luis M. de Campos, José A. Gámez, Serafín Moral:
Partial abductive inference in Bayesian belief networks by simulated annealing. Int. J. Approx. Reason. 27(3): 263-283 (2001) - [j2]Luis M. de Campos, José A. Gámez, Serafín Moral:
Simplifying Explanations in Bayesian Belief Networks. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 9(4): 461-490 (2001)
1990 – 1999
- 1999
- [j1]Luis M. de Campos, José A. Gámez, Serafín Moral:
Partial abductive inference in Bayesian belief networks using a genetic algorithm. Pattern Recognit. Lett. 20(11-13): 1211-1217 (1999)
Coauthor Index
Juan C. Alfaro
aka: Juan Carlos Alfaro Jiménez
aka: Juan Carlos Alfaro Jiménez
Pablo Bermejo 0001
aka: Pablo Bermejo López
aka: Pablo Bermejo López
Luis de la Ossa
aka: Luis delaOssa
aka: Luis delaOssa
[j77] [j76] [c82] [c81] [c80] [c79] [i3] [c78] [c77] [i2] [j71] [j67] [c72] [c67] [c66] [j58] [j56] [c64] [j50] [j49] [j47] [j46] [j45] [c62] [j41] [j40] [j38] [c61] [j37] [c59] [c57] [c54] [e3] [j33] [c53] [c52] [j30] [c50] [c49] [j27] [j26] [c46] [j25] [j23] [j22] [j21] [j19] [j18] [c45] [c43] [c40] [c38] [c36] [c35] [j17] [j16] [c34] [c33] [c31] [c30] [c29] [c26] [c25] [j13] [c23] [c22] [c21] [c20] [c19] [j12] [j10] [c18] [c17] [c15] [p2] [c12] [c10] [c9] [c6] [c5] [j7] [j6] [c1]
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