Partial abductive inference in Bayesian belief networks using a genetic algorithm. - Luis M. de Campos; José A. Gámez 001; Serafín Moral (Pattern Recognit. Lett., 1999)

Accelerating chromosome evaluation for partial abductive inference in Bayesian networks by means of explanation set absorption. - Luis M. de Campos; José A. Gámez 001; Serafín Moral (Int. J. Approx. Reason., 2001)

Partial abductive inference in Bayesian belief networks by simulated annealing. - Luis M. de Campos; José A. Gámez 001; Serafín Moral (Int. J. Approx. Reason., 2001)

Simplifying Explanations in Bayesian Belief Networks. - Luis M. de Campos; José A. Gámez 001; Serafín Moral (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2001)

Partial Abductive Inference in Bayesian Networks: An Empirical Comparison Between GAs and EDAs. - L. M. Campos; José A. Gámez 001; Pedro Larrañaga; Serafín Moral; Txomin Romero (Estimation of Distribution Algorithms, 2002)

Applicability of Estimation of Distribution Algorithms to the Fuzzy Rule Learning Problem: A Preliminary Study. - M. Julia Flores; José A. Gámez 001 (ICEIS, 2002)

Graphical Models to Causal Discovery from Data. - Luis M. de Campos; José A. Gámez 001; José Miguel Puerta (Probabilistic Graphical Models, 2002)

Ant colony optimization for learning Bayesian networks. - Luis M. de Campos; Juan M. Fernández-Luna; José A. Gámez 001; José M. Puerta (Int. J. Approx. Reason., 2002)

Searching for the best elimination sequence in Bayesian networks by using ant colony optimization. - José A. Gámez 001; José M. Puerta (Pattern Recognit. Lett., 2002)

Partial abductive inference in Bayesian belief networks - an evolutionary computation approach by using problem-specific genetic operators. - Luis M. de Campos; José A. Gámez 001; Serafín Moral (IEEE Trans. Evol. Comput., 2002)

Heuristic Based Sampling in Estimation of Distribution Algorithms: An Initial Approach. - Luis de la Ossa; José A. Gámez 001; José M. Puerta (CAEPIA, 2003)

Partial Abductive Inference in Bayesian Networks By Using Probability Trees. - Luis M. de Campos; José A. Gámez 001; Serafín Moral (ICEIS (2), 2003)

Incremental compilation of Bayesian networks. - M. Julia Flores; José A. Gámez 001; Kristian G. Olesen (UAI, 2003)

Triangulation of Bayesian networks by retriangulation. - M. Julia Flores; José A. Gámez 001 (Int. J. Intell. Syst., 2003)

Probabilistic graphical models. - José A. Gámez 001; Antonio Salmerón (Int. J. Intell. Syst., 2003)

A Methodology to Evaluate the Effectiveness of Traffic Balancing Algorithms. - J. E. Villalobos; José L. Sánchez 002; José A. Gámez 001; José Carlos Sancho; Antonio Robles (Euro-Par, 2004)

Migration of Probability Models Instead of Individuals: An Alternative When Applying the Island Model to EDAs. - Luis de la Ossa; José A. Gámez 001; José Miguel Puerta (PPSN, 2004)

Improving model combination through local search in parallel univariate EDAs. - Luis de la Ossa; José A. Gámez 001; José M. Puerta (Congress on Evolutionary Computation, 2005)

Abductive Inference in Bayesian Networks: Finding a Partition of the Explanation Space. - M. Julia Flores; José A. Gámez 001; Serafín Moral (ECSQARU, 2005)

Constrained Score+(Local)Search Methods for Learning Bayesian Networks. - José A. Gámez 001; José Miguel Puerta (ECSQARU, 2005)

Breeding Value Classification in Manchego Sheep: A Study of Attribute Selection and Construction. - M. Julia Flores; José A. Gámez 001 (KES (2), 2005)

Learning Linguistic Fuzzy Rules by Using Estimation of Distribution Algorithms as the Search Engine in the COR Methodology. - M. Julia Flores; José A. Gámez 001; José M. Puerta (Towards a New Evolutionary Computation, 2006)

Learning weighted linguistic fuzzy rules with estimation of distribution algorithms. - Luis delaOssa; José A. Gámez 001; José M. Puerta (IEEE Congress on Evolutionary Computation, 2006)

Improvement in the Performance of Island Based Genetic Algorithms Through Path Relinking. - Luis de la Ossa; José A. Gámez 001; José M. Puerta (Hybrid Metaheuristics, 2006)

The Independency tree model: a new approach for clustering and factorisation. - M. Julia Flores; José A. Gámez 001; Serafín Moral (Probabilistic Graphical Models, 2006)

Dependency networks based classifiers: learning models by using independence. - José A. Gámez 001; Juan L. Mateo; José M. Puerta (Probabilistic Graphical Models, 2006)

Unsupervised naive Bayes for data clustering with mixtures of truncated exponentials. - José A. Gámez 001; Rafael Rumí; Antonio Salmerón (Probabilistic Graphical Models, 2006)

Searching for alignments in SMT. A novel approach based on an Estimation of Distribution Algorithm. - Luis Rodríguez; Ismael García-Varea; José A. Gámez 001 (WMT@HLT-NAACL, 2006)

Seleccion genetica para la mejora de la raza ovina manchega mediante tecnicas de Mineria de Datos. - M. Julia Flores; José A. Gámez 001; Juan L. Mateo; José M. Puerta (Inteligencia Artif., 2006)

Special issue on PGM'04: Second European workshop on probabilistic graphical models 2004. - Peter J. F. Lucas; José A. Gámez 001; Antonio Salmerón (Int. J. Approx. Reason., 2006)

Initial approaches to the application of islands-based parallel EDAs in continuous domains. - Luis de la Ossa; José A. Gámez 001; José M. Puerta (J. Parallel Distributed Comput., 2006)

A Fast Hill-Climbing Algorithm for Bayesian Networks Structure Learning. - José A. Gámez 001; Juan L. Mateo; José M. Puerta (ECSQARU, 2007)

Learning Bayesian Classifiers from Dependency Network Classifiers. - José A. Gámez 001; Juan L. Mateo; José M. Puerta (ICANNGA (1), 2007)

Attribute Construction for E-Mail Foldering by Using Wrappered Forward Greedy Search. - Pablo Bermejo 001; José A. Gámez 001; José M. Puerta (ICEIS (2), 2007)

EDNA: Estimation of Dependency Networks Algorithm. - José A. Gámez 001; Juan L. Mateo; José M. Puerta (IWINAC (1), 2007)

Improving Revisitation Browsers Capability by Using a Dynamic Bookmarks Personal Toolbar. - José A. Gámez 001; Juan L. Mateo; José M. Puerta (WISE, 2007)

Initial breeding value prediction on Manchego sheep by using rule-based systems. - Luis de la Ossa; M. Julia Flores; José A. Gámez 001; Juan L. Mateo; José M. Puerta (Expert Syst. Appl., 2007)

Improvement of a car racing controller by means of Ant Colony Optimization algorithms. - Luis delaOssa; José A. Gámez 001; Verónica López (CIG, 2008)

Improved EDNA (estimation of dependency networks algorithm) using combining function with bivariate probability distributions. - José A. Gámez 001; Juan L. Mateo; José M. Puerta (GECCO, 2008)

Gait Optimization in AIBO Robots Using an Estimation of Distribution Algorithm. - Juan Ignacio Alonso-Barba; José A. Gámez 001; José Miguel Puerta; Ismael García-Varea (HIS, 2008)

An improved Markov-based localization approach by using image quality evaluation. - José A. Gámez 001; Ismael García-Varea; Jesus Martínez-Gómez (ICARCV, 2008)

On the application of different evolutionary algorithms to the alignment problem in statistical machine translation. - Luis Rodríguez; Ismael García-Varea; José A. Gámez 001 (Neurocomputing, 2008)

Low-Complexity Heterogeneous Video Transcoding Using Data Mining. - Gerardo Fernández-Escribano; Jens Bialkowski; José A. Gámez 001; Hari Kalva; Pedro Cuenca 001; Luis Orozco-Barbosa; André Kaup (IEEE Trans. Multim., 2008)

Use of Explanation Treesto Describe the State Space of a Probabilistic-Based Abduction Problem. - M. Julia Flores; José A. Gámez 001; Serafín Moral (Innovations in Bayesian Networks, 2008)

Avoiding premature convergence in estimation of distribution algorithms. - Luis de la Ossa; José A. Gámez 001; Juan L. Mateo; José M. Puerta (IEEE Congress on Evolutionary Computation, 2009)

Incremental Wrapper-based subset Selection with replacement: An advantageous alternative to sequential forward selection. - Pablo Bermejo 001; José A. Gámez 001; José M. Puerta (CIDM, 2009)

The PDG-Mixture Model for Clustering. - M. Julia Flores; José A. Gámez 001; Jens Dalgaard Nielsen (DaWaK, 2009)

HODE: Hidden One-Dependence Estimator. - M. Julia Flores; José A. Gámez 001; Ana M. Martínez; José M. Puerta (ECSQARU, 2009)

GAODE and HAODE: two proposals based on AODE to deal with continuous variables. - M. Julia Flores; José A. Gámez 001; Ana M. Martínez; José M. Puerta (ICML, 2009)

Comparison of balancing techniques for multimedia IR over imbalanced datasets. - Pablo Bermejo 001; Frank Hopfgartner; José A. Gámez 001; José M. Puerta; Joemon M. Jose (ISCIS, 2009)

Using Genetic Algorithms for Real-Time Object Detection. - Jesus Martínez-Gómez; José A. Gámez 001; Ismael García-Varea; Vicente Matellán (RoboCup, 2009)

Learning weighted linguistic fuzzy rules by using specifically-tailored hybrid estimation of distribution algorithms. - Luis de la Ossa; José A. Gámez 001; José M. Puerta (Int. J. Approx. Reason., 2009)

Evolutionary and metaheuristics based data mining. - María José del Jesus; José A. Gámez 001; José M. Puerta (Soft Comput., 2009)

Comparing Cellular and Panmictic Genetic Algorithms for Real-Time Object Detection. - Jesus Martínez-Gómez; José A. Gámez 001; Ismael García-Varea (EvoApplications (1), 2010)

Learning cooperative linguistic fuzzy rules using fast local search algorithms. - Luis delaOssa; José A. Gámez 001; José M. Puerta (FUZZ-IEEE, 2010)

Combining Image Invariant Features and Clustering Techniques for Visual Place Classification. - Jesus Martínez-Gómez; Alejandro Jiménez-Picazo; José A. Gámez 001; Ismael García-Varea (ICPR Contests, 2010)

Improving Incremental Wrapper-Based Feature Subset Selection by Using Re-ranking. - Pablo Bermejo 001; José A. Gámez 001; José M. Puerta (IEA/AIE (1), 2010)

Analyzing the Impact of the Discretization Method When Comparing Bayesian Classifiers. - M. Julia Flores; José A. Gámez 001; Ana M. Martínez; José M. Puerta (IEA/AIE (1), 2010)

Flexible learning of k-dependence Bayesian network classifiers. - Arcadio Rubio; José Antonio Gámez (GECCO, 2011)

Enhancing Incremental Feature Subset Selection in High-Dimensional Databases by Adding a Backward Step. - Pablo Bermejo 001; Luis de la Ossa; José A. Gámez 001; José M. Puerta (ISCIS, 2011)

A study on different backward feature selection criteria over high-dimensional databases. - Pablo Bermejo 001; Luis de la Ossa; José A. Gámez 001; José M. Puerta (ISDA, 2011)

Learning heterogeneus cooperative linguistic fuzzy rules using local search: Enhancing the COR search space. - Javier Cózar; Luis delaOssa; José A. Gámez 001 (ISDA, 2011)

Mixture of truncated exponentials in supervised classification: Case study for the naive bayes and averaged one-dependence estimators classifiers. - M. Julia Flores; José A. Gámez 001; Ana M. Martínez; Antonio Salmerón (ISDA, 2011)

Handling numeric attributes when comparing Bayesian network classifiers: does the discretization method matter? - M. Julia Flores; José A. Gámez 001; Ana M. Martínez; José M. Puerta (Appl. Intell., 2011)

The impact of soft computing for the progress of artificial intelligence. - Oscar Cordón; Antonio Fernández-Caballero 001; José A. Gámez 001; Frank Hoffmann 001 (Appl. Soft Comput., 2011)

Learning Bayesian networks by hill climbing: efficient methods based on progressive restriction of the neighborhood. - José A. Gámez 001; Juan L. Mateo; José M. Puerta (Data Min. Knowl. Discov., 2011)

Improving the performance of Naive Bayes multinomial in e-mail foldering by introducing distribution-based balance of datasets. - Pablo Bermejo 001; José A. Gámez 001; José M. Puerta (Expert Syst. Appl., 2011)

Improving Incremental Wrapper-Based Subset Selection via Replacement and Early Stopping. - Pablo Bermejo 001; José A. Gámez 001; José M. Puerta (Int. J. Pattern Recognit. Artif. Intell., 2011)

Incremental Compilation of Bayesian Networks Based on Maximal Prime Subgraphs. - M. Julia Flores; José A. Gámez 001; Kristian G. Olesen (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2011)

A GRASP algorithm for fast hybrid (filter-wrapper) feature subset selection in high-dimensional datasets. - Pablo Bermejo 001; José A. Gámez 001; José M. Puerta (Pattern Recognit. Lett., 2011)

On the discovery of association rules by means of evolutionary algorithms. - María José del Jesus; José A. Gámez 001; Pedro González 001; José M. Puerta (WIREs Data Mining Knowl. Discov., 2011)

Non-Disjoint Discretization for Aggregating One-Dependence Estimator Classifiers. - Ana M. Martínez; Geoffrey I. Webb; M. Julia Flores; José A. Gámez 001 (HAIS (2), 2012)

Evaluation of a Thermal-Comfort Control System Using Real Data. - Pablo Bermejo 001; Luis Redondo; Luis delaOssa; Daniel Rodríguez; M. Julia Flores; Carmen Urea; José A. Gámez 001; Jesus Martínez-Gómez; José M. Puerta (KES, 2012)

Modelling and inference with Conditional Gaussian Probabilistic Decision Graphs. - Jens Dalgaard Nielsen; José A. Gámez 001; Antonio Salmerón (Int. J. Approx. Reason., 2012)

Fast wrapper feature subset selection in high-dimensional datasets by means of filter re-ranking. - Pablo Bermejo 001; Luis de la Ossa; José A. Gámez 001; José M. Puerta (Knowl. Based Syst., 2012)

One iteration CHC algorithm for learning Bayesian networks: an effective and efficient algorithm for high dimensional problems. - José A. Gámez 001; Juan L. Mateo; José M. Puerta (Prog. Artif. Intell., 2012)

Single- and Multi-label Prediction of Burden on Families of Schizophrenia Patients. - Pablo Bermejo 001; Marta Lucas; José A. Rodríguez-Montes; Pedro J. Tárraga; Javier Lucas; José A. Gámez 001; José M. Puerta (AIME, 2013)

Learning more Accurate Bayesian Networks in the CHC Approach by Adjusting the Trade-Off between Efficiency and Accuracy. - Jacinto Arias; José A. Gámez 001; José M. Puerta (CAEPIA, 2013)

Computing the Consensus Permutation in Mallows Distribution by Using Genetic Algorithms. - Juan A. Aledo; José A. Gámez 001; David Molina (IEA/AIE, 2013)

Tackling the rank aggregation problem with evolutionary algorithms. - Juan A. Aledo; José A. Gámez 001; David Molina (Appl. Math. Comput., 2013)

Scaling up the Greedy Equivalence Search algorithm by constraining the search space of equivalence classes. - Juan Ignacio Alonso-Barba; Luis delaOssa; José A. Gámez 001; José M. Puerta (Int. J. Approx. Reason., 2013)

Obtaining the optimal configuration of high-radix Combined switches. - Juan A. Villar; Francisco J. Andujar; José L. Sánchez 002; Francisco J. Alfaro; José A. Gámez 001; José Duato (J. Parallel Distributed Comput., 2013)

Fast quadtree level decision algorithm for H.264/HEVC transcoder. - Antonio Jesús Díaz-Honrubia; José Luis Martínez 001; José M. Puerta; José A. Gámez 001; Jan De Cock; Pedro Cuenca 001 (ICIP, 2014)

A Pairwise Class Interaction Framework for Multilabel Classification. - Jacinto Arias; José A. Gámez 001; Thomas D. Nielsen; José M. Puerta (Probabilistic Graphical Models, 2014)

TSK-0 Fuzzy Rule-Based Systems for High-Dimensional Problems Using the Apriori Principle for Rule Generation. - Javier Cózar; Luis de la Ossa; José A. Gámez 001 (RSCTC, 2014)

Learning TSK-0 linguistic fuzzy rules by means of local search algorithms. - Javier Cózar; Luis de la Ossa; José A. Gámez 001 (Appl. Soft Comput., 2014)

A tool based on Bayesian networks for supporting geneticists in plant improvement by controlled pollination. - Jens Dalgaard Nielsen; Antonio Salmerón; José A. Gámez 001 (Int. J. Approx. Reason., 2014)

Domains of competence of the semi-naive Bayesian network classifiers. - M. Julia Flores; José A. Gámez 001; Ana M. Martínez (Inf. Sci., 2014)

Speeding up incremental wrapper feature subset selection with Naive Bayes classifier. - Pablo Bermejo 001; José A. Gámez 001; José M. Puerta (Knowl. Based Syst., 2014)

Data clustering using hidden variables in hybrid Bayesian networks. - Antonio Fernández 002; José A. Gámez 001; Rafael Rumí; Antonio Salmerón (Prog. Artif. Intell., 2014)

A Data-Driven Probabilistic CTU Splitting Algorithm for Fast H.264/HEVC Video Transcoding. - Antonio Jesús Díaz-Honrubia; José Luis Martínez 001; Pedro Cuenca 001; José Antonio Gámez; José Miguel Puerta (DCC, 2015)

Comparing TSK-1 FRBS against SVR for electrical power prediction in buildings. - Javier Cózar; Gonzalo Vergara; José A. Gámez 001; Emilio Soria-Olivas (IFSA-EUSFLAT, 2015)

Ant Colony and Surrogate Tree-Structured Models for Orderings-Based Bayesian Network Learning. - Juan Ignacio Alonso-Barba; Luis de la Ossa; Olivier Regnier-Coudert; John A. W. McCall; José A. Gámez 001; José M. Puerta (GECCO, 2015)

Impact on Bayesian Networks Classifiers When Learning from Imbalanced Datasets. - M. Julia Flores; José A. Gámez 001 (ICAART (2), 2015)

Comparing ELM Against MLP for Electrical Power Prediction in Buildings. - Gonzalo Vergara; Javier Cózar; Cristina Romero-González; José A. Gámez 001; Emilio Soria-Olivas (IWINAC (2), 2015)

Scalable Learning of k-dependence Bayesian Classifiers under MapReduce. - Jacinto Arias; José A. Gámez 001; José M. Puerta (TrustCom/BigDataSE/ISPA (2), 2015)

Structural Learning of Bayesian Networks Via Constrained Hill Climbing Algorithms: Adjusting Trade-off between Efficiency and Accuracy. - Jacinto Arias; José A. Gámez 001; José M. Puerta (Int. J. Intell. Syst., 2015)

Construction of a Semi-Naive Model to Predict Early Readmission of COPD Patients by Using Quality Care Information. - Pablo Bermejo 001; José A. Gámez 001; José M. Puerta; Marco A. Esquivias; Pedro J. Tárraga (ICDM Workshops, 2016)

FSS-OBOP: Feature subset selection guided by a bucket order consensus ranking. - Juan A. Aledo; José A. Gámez 001; David Molina; Alejandro Rosete (SSCI, 2016)

Using extension sets to aggregate partial rankings in a flexible setting. - Juan A. Aledo; José A. Gámez 001; David Molina (Appl. Math. Comput., 2016)

Using metaheuristic algorithms for parameter estimation in generalized Mallows models. - Juan A. Aledo; José A. Gámez 001; David Molina (Appl. Soft Comput., 2016)

Medical image modality classification using discrete Bayesian networks. - Jacinto Arias; Jesus Martínez-Gómez; José A. Gámez 001; Alba Garcia Seco de Herrera; Henning Müller (Comput. Vis. Image Underst., 2016)

A scalable pairwise class interaction framework for multidimensional classification. - Jacinto Arias; José A. Gámez 001; Thomas D. Nielsen; José M. Puerta (Int. J. Approx. Reason., 2016)

Low-complexity heterogeneous architecture for H.264/HEVC video transcoding. - Antonio Jesús Díaz-Honrubia; Gabriel Cebrián-Márquez; José Luis Martínez 001; Pedro Cuenca 001; José Miguel Puerta; José Antonio Gámez (J. Real Time Image Process., 2016)

Random extreme learning machines to predict electric load in buildings. - Gonzalo Vergara; Juan Ignacio Alonso-Barba; Emilio Soria-Olivas; José A. Gámez 001; Manuel Domínguez 002 (Prog. Artif. Intell., 2016)

Adaptive Fast Quadtree Level Decision Algorithm for H.264 to HEVC Video Transcoding. - Antonio Jesús Díaz-Honrubia; José Luis Martínez 001; Pedro Cuenca 001; José Antonio Gámez; José Miguel Puerta (IEEE Trans. Circuits Syst. Video Technol., 2016)

Generation of first-order TSK rules based on the apriori + search approach. - Javier Cózar; Luis de la Ossa; José A. Gámez 001 (CEC, 2017)

OC1-DE: A Differential Evolution Based Approach for Inducing Oblique Decision Trees. - Rafael Rivera-López; Juana Canul-Reich; José A. Gámez 001; José M. Puerta (ICAISC (1), 2017)

Partial evaluation in Rank Aggregation Problems. - Juan A. Aledo; José A. Gámez 001; Alejandro Rosete (Comput. Oper. Res., 2017)

Utopia in the solution of the Bucket Order Problem. - Juan A. Aledo; José A. Gámez 001; Alejandro Rosete (Decis. Support Syst., 2017)

An Application of Dynamic Bayesian Networks to Condition Monitoring and Fault Prediction in a Sensored System: a Case Study. - Javier Cózar; José M. Puerta; José A. Gámez 001 (Int. J. Comput. Intell. Syst., 2017)

Guest Editorial: Recent Trends in Intelligent Systems. - José A. Gámez 001; Francisco Herrera; José M. Puerta (Int. J. Intell. Syst., 2017)

Tackling the supervised label ranking problem by bagging weak learners. - Juan A. Aledo; José A. Gámez 001; David Molina (Inf. Fusion, 2017)

Volume, variety and velocity in Data Science. - Amparo Alonso-Betanzos; José A. Gámez 001; Francisco Herrera; José M. Puerta; José C. Riquelme (Knowl. Based Syst., 2017)

Learning distributed discrete Bayesian Network Classifiers under MapReduce with Apache Spark. - Jacinto Arias; José A. Gámez 001; José M. Puerta (Knowl. Based Syst., 2017)

CTU splitting algorithm for H.264/AVC and HEVC simultaneous encoding. - Antonio Jesús Díaz-Honrubia; Johan De Praeter; Glenn Van Wallendael; José Luis Martínez 001; Pedro Cuenca 001; José M. Puerta; José A. Gámez 001 (J. Supercomput., 2017)

CGLAD: Using GLAD in Crowdsourced Large Datasets. - Enrique González Rodrigo; Juan A. Aledo; José A. Gámez 001 (IDEAL (1), 2018)

Bayesian Network Classifiers Under the Ensemble Perspective. - Jacinto Arias; José A. Gámez 001; José M. Puerta (PGM, 2018)

On the use of local search heuristics to improve GES-based Bayesian network learning. - Juan Ignacio Alonso-Barba; Luis de la Ossa; José A. Gámez 001; José M. Puerta (Appl. Soft Comput., 2018)

Approaching rank aggregation problems by using evolution strategies: The case of the optimal bucket order problem. - Juan A. Aledo; José A. Gámez 001; Alejandro Rosete (Eur. J. Oper. Res., 2018)

Adapting the CMIM algorithm for multilabel feature selection. A comparison with existing methods. - Pablo Bermejo 001; José A. Gámez 001; José M. Puerta (Expert Syst. J. Knowl. Eng., 2018)

Learning compact zero-order TSK fuzzy rule-based systems for high-dimensional problems using an Apriori + local search approach. - Javier Cózar; Luis delaOssa; José A. Gámez 001 (Inf. Sci., 2018)

Consensus-based journal rankings: A complementary tool for bibliometric evaluation. - Juan A. Aledo; José A. Gámez 001; David Molina; Alejandro Rosete (J. Assoc. Inf. Sci. Technol., 2018)

Building efficient fuzzy regression trees for large scale and high dimensional problems. - Javier Cózar; Francesco Marcelloni; José A. Gámez 001; Luis de la Ossa (J. Big Data, 2018)

A Probabilistic Graphical Model-Based Approach for the Label Ranking Problem. - Juan Carlos Alfaro Jiménez; Enrique González Rodrigo; Juan A. Aledo; José Antonio Gámez (ECSQARU, 2019)

Structural Fusion/Aggregation of Bayesian Networks via Greedy Equivalence Search Learning Algorithm. - José M. Puerta; Juan A. Aledo; José Antonio Gámez; Jorge D. Laborda (ECSQARU, 2019)

CiDAEN: An Online Data Science Course. - Luis de la Ossa; Pablo Bermejo 001; Juan A. Aledo; José A. Gámez 001; José M. Puerta; Cristina Romero-González; Jacinto Arias; Javier Cózar; Enrique González Rodrigo; Juan Ignacio Alonso-Barba; Jesus Martínez-Gómez (HELMeTO, 2019)

Approaching the rank aggregation problem by local search-based metaheuristics. - Juan A. Aledo; José A. Gámez 001; David Molina (J. Comput. Appl. Math., 2019)

spark-crowd: A Spark Package for Learning from Crowdsourced Big Data. - Enrique González Rodrigo; Juan A. Aledo; José A. Gámez 001 (J. Mach. Learn. Res., 2019)

Scaling up the learning-from-crowds GLAD algorithm using instance-difficulty clustering. - Enrique González Rodrigo; Juan A. Aledo; José A. Gámez 001 (Prog. Artif. Intell., 2019)

A Metahierarchical Rule Decision System to Design Robust Fuzzy Classifiers Based on Data Complexity. - Javier Cózar; Alberto Fernández 001; Francisco Herrera; José A. Gámez 001 (IEEE Trans. Fuzzy Syst., 2019)

Machine learning from crowds: A systematic review of its applications. - Enrique González Rodrigo; Juan A. Aledo; José A. Gámez 001 (WIREs Data Mining Knowl. Discov., 2019)

Averaging-Based Ensemble Methods for the Partial Label Ranking Problem. - Juan C. Alfaro; Juan A. Aledo; José A. Gámez 001 (HAIS, 2020)

Economic modelling of robotic disassembly in end-of-life product recovery for remanufacturing. - F. Javier Ramírez; Juan A. Aledo; José A. Gámez 001; Duc Truong Pham (Comput. Ind. Eng., 2020)

STree: A Single Multi-class Oblique Decision Tree Based on Support Vector Machines. - Ricardo Montañana; José A. Gámez 001; José M. Puerta (CAEPIA, 2021)

Mixture-Based Probabilistic Graphical Models for the Partial Label Ranking Problem. - Juan C. Alfaro; Juan A. Aledo; José A. Gámez 001 (IDEAL, 2021)

A Data-Driven Approach for Components Useful Life Estimation in Wind Turbines. - Alejandro Zornoza Martínez; Jesus Martínez-Gómez; José A. Gámez 001 (SOCO, 2021)

Mixture-Based Probabilistic Graphical Models for the Label Ranking Problem. - Enrique González Rodrigo; Juan C. Alfaro; Juan A. Aledo; José A. Gámez 001 (Entropy, 2021)

Learning decision trees for the partial label ranking problem. - Juan C. Alfaro; Juan A. Aledo; José A. Gámez 001 (Int. J. Intell. Syst., 2021)

Efficient and accurate structural fusion of Bayesian networks. - José M. Puerta; Juan A. Aledo; José A. Gámez 001; Jorge D. Laborda (Inf. Fusion, 2021)

A highly scalable algorithm for weak rankings aggregation. - Juan A. Aledo; José A. Gámez 001; Alejandro Rosete (Inf. Sci., 2021)

Introduction to the special issue of the ECML PKDD 2021 journal track. - Annalisa Appice; Sergio Escalera; José A. Gámez 001; Heike Trautmann (Mach. Learn., 2021)

GRASP-Based Hybrid Search to Solve the Multi-objective Requirements Selection Problem. - Víctor Pérez-Piqueras; Pablo Bermejo López; José A. Gámez 001 (OLA, 2022)

Integrating Bayesian network classifiers to deal with the partial label ranking problem. - Juan C. Alfaro; Juan A. Aledo; José A. Gámez 001 (PGM, 2022)

Estimation of Distribution Algorithms Applied to the Next Release Problem. - Víctor Pérez-Piqueras; Pablo Bermejo López; José A. Gámez 001 (SOCO, 2022)

Factual and Counterfactual Explanations in Fuzzy Classification Trees. - Guillermo Fernández 005; Juan A. Aledo; José Antonio Gámez; José M. Puerta (IEEE Trans. Fuzzy Syst., 2022)

MiniAnDE: A Reduced AnDE Ensemble to Deal with Microarray Data. - Pablo Torrijos; José A. Gámez 001; José M. Puerta (EANN, 2023)

A Ring-Based Distributed Algorithm for Learning High-Dimensional Bayesian Networks. - Jorge D. Laborda; Pablo Torrijos; José M. Puerta; José A. Gámez 001 (ECSQARU, 2023)

Hybrid Multi-Objective Relinked GRASP for the constrained Next Release Problem. - Víctor Pérez-Piqueras; Pablo Bermejo 001; José A. Gámez 001 (TrustCom, 2023)

FEDA-NRP: A fixed-structure multivariate estimation of distribution algorithm to solve the multi-objective Next Release Problem with requirements interactions. - Víctor Pérez-Piqueras; Pablo Bermejo 001; José A. Gámez 001 (Eng. Appl. Artif. Intell., 2023)

Pairwise learning for the partial label ranking problem. - Juan C. Alfaro; Juan A. Aledo; José A. Gámez 001 (Pattern Recognit., 2023)

Multi-dimensional Bayesian network classifiers for partial label ranking. - Juan C. Alfaro; Juan A. Aledo; José A. Gámez 001 (Int. J. Approx. Reason., 2023)

Structural Fusion of Bayesian Networks with Limited Treewidth Using Genetic Algorithms. - Pablo Torrijos; José A. Gámez 001; José M. Puerta (CEC, 2024)

FedGES: A Federated Learning Approach for Bayesian Network Structure Learning. - Pablo Torrijos; José A. Gámez 001; José M. Puerta (DS (2), 2024)

A User Study on the Utility of Context-Aware Explanations for Assisting Data Scientists in Error Analysis of Fuzzy Decision Trees. - Guillermo Fernández 005; José A. Gámez 001; José M. Puerta; Juan A. Aledo; Jose Maria Alonso-Moral; Alberto Bugarín (FUZZ, 2024)

FLocalX - Local to Global Fuzzy Explanations for Black Box Classifiers. - Guillermo Fernández 005; Riccardo Guidotti; Fosca Giannotti; Mattia Setzu; Juan A. Aledo; José A. Gámez 001; José M. Puerta (IDA (2), 2024)

Federated Learning with Discriminative Naive Bayes Classifier. - Pablo Torrijos; Juan C. Alfaro; José A. Gámez 001; José M. Puerta (IDEAL (2), 2024)

Enhancing Bayesian Network Structural Learning with Monte Carlo Tree Search. - Jorge D. Laborda; Pablo Torrijos; José M. Puerta; José A. Gámez 001 (IPMU (1), 2024)

Distributed fusion-based algorithms for learning high-dimensional Bayesian Networks: Testing ring and star topologies. - Jorge D. Laborda; Pablo Torrijos; José M. Puerta; José A. Gámez 001 (Int. J. Approx. Reason., 2024)

Parallel structural learning of Bayesian networks: Iterative divide and conquer algorithm based on structural fusion. - Jorge D. Laborda; Pablo Torrijos; José M. Puerta; José A. Gámez 001 (Knowl. Based Syst., 2024)

Label ranking oblique trees. - Enrique González Rodrigo; Juan C. Alfaro; Juan A. Aledo; José A. Gámez 001 (Knowl. Based Syst., 2024)

Efficient ensembles of distance-based label ranking trees. - Enrique González Rodrigo; Juan C. Alfaro; Juan A. Aledo; José A. Gámez 001 (Expert Syst. J. Knowl. Eng., 2024)

Agile Effort Estimation Improved by Feature Selection and Model Explainability. - Víctor Pérez-Piqueras; Pablo Bermejo López; José A. Gámez 001 (ENASE, 2025)

Genetic Algorithms for Tractable Bayesian Network Fusion via Pre-Fusion Edge Pruning. - Pablo Torrijos; José A. Gámez 001; José M. Puerta; Juan A. Aledo (GECCO, 2025)

ODTE - An ensemble of multi-class SVM-based oblique decision trees. - Ricardo Montañana; José A. Gámez 001; José M. Puerta (Expert Syst. Appl., 2025)

A consensus set for the aggregation of partial rankings: The case of the Optimal Set of Bucket Orders Problem. - Juan A. Aledo; José A. Gámez 001; Alejandro Rosete (Inf. Fusion, 2025)

FedGES: A Federated Learning Approach for BN Structure Learning. - Pablo Torrijos; José A. Gámez 001; José M. Puerta (CoRR, 2025)

Informed Greedy Algorithm for Scalable Bayesian Network Fusion via Minimum Cut Analysis. - Pablo Torrijos; José M. Puerta; José A. Gámez 001; Juan A. Aledo (CoRR, 2025)