J. M. Puerta

发表

Probabilistic Graphical Models PGM Prague 2018

Thorsten J. Ottosen, J. Peña, F. Díez, 2018 .

Aalborg Universitet Robust classification using mixtures of dependency networks

Thomas D. Nielsen, J. L. Mateo, J. A. Gámez, 2008 .

An iterated local search algorithm for learning Bayesian networks with restarts based on conditional independence tests

Jose Miguel Puerta, Luis M. de Campos, Juan M. Fernández-Luna, 2003, Int. J. Intell. Syst..

Proceedings of the 16th Conference of the Spanish Association for Artificial Intelligence on Advances in Artificial Intelligence - Volume 9422

José A. Gámez, Mikel Galar, Bernabé Dorronsoro, 2015 .

Graphical Models to Causal Discovery from Data

Jose Miguel Puerta, José A. Gámez, Luis M. de Campos, 2002, Probabilistic Graphical Models.

One iteration CHC algorithm for learning Bayesian networks: an effective and efficient algorithm for high dimensional problems

J. L. Mateo, J. M. Puerta, J. A. Gamez, 2012, Progress in Artificial Intelligence.

A Fast Hill-Climbing Algorithm for Bayesian Networks Structure Learning

Jose Miguel Puerta, José A. Gámez, Juan L. Mateo, 2007, ECSQARU.

Design and simulation of a thermal comfort adaptive system based on fuzzy logic and on-line learning

Luis de la Ossa, José M. Puerta, Pablo Bermejo, 2012 .

Learning Cooperative TSK-0 Fuzzy Rules Using Fast Local Search Algorithms

Jose Miguel Puerta, Javier Cózar, Luis de la Ossa, 2011, CAEPIA.

Learning cooperative linguistic fuzzy rules using fast local search algorithms

Jose Miguel Puerta, José A. Gámez, Luis de la Ossa, 2010, International Conference on Fuzzy Systems.

Learning weighted linguistic fuzzy rules by using specifically-tailored hybrid estimation of distribution algorithms

Jose Miguel Puerta, José A. Gámez, Luis de la Ossa, 2009, Int. J. Approx. Reason..

Initial breeding value prediction on Manchego sheep by using rule-based systems

Jose Miguel Puerta, José A. Gámez, Juan L. Mateo, 2007, Expert Syst. Appl..

Learning weighted linguistic fuzzy rules with estimation of distribution algorithms

Jose Miguel Puerta, José A. Gámez, Luis de la Ossa, 2006, 2006 IEEE International Conference on Evolutionary Computation.

Learning Linguistic Fuzzy Rules by Using Estimation of Distribution Algorithms as the Search Engine in the COR Methodology

José M. Puerta, M. Julia Flores, José A. Gámez, 2006, Towards a New Evolutionary Computation.

Learning Bayesian networks by hill climbing: efficient methods based on progressive restriction of the neighborhood

Jose Miguel Puerta, José A. Gámez, Juan L. Mateo, 2010, Data Mining and Knowledge Discovery.

Improving Incremental Wrapper-Based Subset Selection via Replacement and Early Stopping

Jose Miguel Puerta, José A. Gámez, Pablo Bermejo, 2011, Int. J. Pattern Recognit. Artif. Intell..

A study on different backward feature selection criteria over high-dimensional databases

Jose Miguel Puerta, José A. Gámez, Luis de la Ossa, 2011, 2011 11th International Conference on Intelligent Systems Design and Applications.

A GRASP algorithm for fast hybrid (filter-wrapper) feature subset selection in high-dimensional datasets

Jose Miguel Puerta, José A. Gámez, Pablo Bermejo, 2011, Pattern Recognit. Lett..

Volume, variety and velocity in Data Science

Jose Miguel Puerta, José A. Gámez, Amparo Alonso-Betanzos, 2017, Knowledge-Based Systems.

Handling numeric attributes when comparing Bayesian network classifiers: does the discretization method matter?

Jose Miguel Puerta, José A. Gámez, Ana M. Martínez, 2011, Applied Intelligence.

Dependency networks based classifiers: learning models by using independence

Jose Miguel Puerta, José A. Gámez, Juan L. Mateo, 2006, Probabilistic Graphical Models.

Avoiding premature convergence in estimation of distribution algorithms

Jose Miguel Puerta, José A. Gámez, Juan L. Mateo, 2009, 2009 IEEE Congress on Evolutionary Computation.

Searching for the best elimination sequence in Bayesian networks by using ant colony optimization

Jose Miguel Puerta, José A. Gámez, J. M. Puerta, 2002, Pattern Recognit. Lett..

Efficient and accurate structural fusion of Bayesian networks

Juan A. Aledo, José A. Gámez, José M. Puerta, 2021, Inf. Fusion.

Global Feature Subset Selection on High-Dimensional Datasets Using Re-ranking-based EDAs

Jose Miguel Puerta, Luis de la Ossa, Pablo Bermejo, 2011, CAEPIA.

A Bayesian Network approach to study the relationships between several neuromuscular performance measures and dynamic postural control in futsal players

Iñaki Ruiz-Pérez, Francisco Ayala, José Miguel Puerta, 2019, PloS one.

A Preventive Model for Muscle Injuries: A Novel Approach based on Learning Algorithms

G. Myer, A. López-Valenciano, F. Ayala, 2017, Medicine and science in sports and exercise.

Speeding up incremental wrapper feature subset selection with Naive Bayes classifier

Jose Miguel Puerta, José A. Gámez, Pablo Bermejo, 2014, Knowl. Based Syst..

Improving the performance of Naive Bayes multinomial in e-mail foldering by introducing distribution-based balance of datasets

Jose Miguel Puerta, José A. Gámez, Pablo Bermejo, 2011, Expert Syst. Appl..

Ant colony optimization for learning Bayesian networks

Jose Miguel Puerta, José A. Gámez, Luis M. de Campos, 2002, Int. J. Approx. Reason..

On the discovery of association rules by means of evolutionary algorithms

María José del Jesús, Jose Miguel Puerta, José A. Gámez, 2011, WIREs Data Mining Knowl. Discov..

Construction of a Semi-Naive Model to Predict Early Readmission of COPD Patients by Using Quality Care Information

Jose Miguel Puerta, José A. Gámez, Pablo Bermejo, 2016, 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW).

Comparison of balancing techniques for multimedia IR over imbalanced datasets

Jose Miguel Puerta, José A. Gámez, Frank Hopfgartner, 2009, 2009 24th International Symposium on Computer and Information Sciences.

On the use of local search heuristics to improve GES-based Bayesian network learning

Jose Miguel Puerta, José A. Gámez, Luis de la Ossa, 2018, Appl. Soft Comput..

Attribute Construction for E-Mail Foldering by Using Wrappered Forward Greedy Search

Jose Miguel Puerta, José A. Gámez, Pablo Bermejo, 2007, ICEIS.

Scaling up the Greedy Equivalence Search algorithm by constraining the search space of equivalence classes

Jose Miguel Puerta, José A. Gámez, Luis de la Ossa, 2011, Int. J. Approx. Reason..

Drawing a baseline in aesthetic quality assessment

M. Julia Flores, Fernando Rubio, Jose M. Puerta, 2018, International Conference on Machine Vision.

Learning distributed discrete Bayesian Network Classifiers under MapReduce with Apache Spark

Jose Miguel Puerta, José A. Gámez, Jacinto Arias, 2017, Knowl. Based Syst..

A scalable pairwise class interaction framework for multidimensional classification

Jose Miguel Puerta, José A. Gámez, Thomas D. Nielsen, 2016, Int. J. Approx. Reason..

Improved EDNA (estimation of dependency networks algorithm) using combining function with bivariate probability distributions

Jose Miguel Puerta, José A. Gámez, Juan L. Mateo, 2008, GECCO '08.

Adaptive Fast Quadtree Level Decision Algorithm for H.264 to HEVC Video Transcoding

Pedro Cuenca, Jose Miguel Puerta, Jose Luis Martinez, 2016, IEEE Transactions on Circuits and Systems for Video Technology.

Local Search Methods for Learning Bayesian Networks Using a Modified Neighborhood in the Space of DAGs

Jose Miguel Puerta, Luis M. de Campos, Juan M. Fernández-Luna, 2002, IBERAMIA.

Adapting the CMIM algorithm for multilabel feature selection. A comparison with existing methods

José A. Gámez, José M. Puerta, Pablo Bermejo, 2018, Expert Syst. J. Knowl. Eng..

Advances in Artificial Intelligence

Mikel Galar, José M. Puerta, Bruno Baruque, 2015, Lecture Notes in Computer Science.

Initial approaches to the application of islands-based parallel EDAs in continuous domains

Jose Miguel Puerta, José A. Gámez, Luis de la Ossa, 2005, 2005 International Conference on Parallel Processing Workshops (ICPPW'05).

An Application of Dynamic Bayesian Networks to Condition Monitoring and Fault Prediction in a Sensored System: a Case Study

Jose Miguel Puerta, José A. Gámez, Javier Cózar, 2017, Int. J. Comput. Intell. Syst..

Fast wrapper feature subset selection in high-dimensional datasets by means of filter re-ranking

Jose Miguel Puerta, José A. Gámez, Luis de la Ossa, 2012, Knowl. Based Syst..

Automatic quantification of the subcellular localization of chimeric GFP protein supported by a two-level Naive Bayes classifier

Jose Miguel Puerta, Luis de la Ossa, Juan Ignacio Alonso-Barba, 2015, Expert Syst. Appl..

OC1-DE: A Differential Evolution Based Approach for Inducing Oblique Decision Trees

Jose Miguel Puerta, José A. Gámez, Rafael Rivera-López, 2017, ICAISC.

Migration of Probability Models Instead of Individuals: An Alternative When Applying the Island Model to EDAs

Jose Miguel Puerta, José A. Gámez, Luis de la Ossa, 2004, PPSN.

A Pairwise Class Interaction Framework for Multilabel Classification

Jose Miguel Puerta, José A. Gámez, Thomas D. Nielsen, 2014, Probabilistic Graphical Models.

Improving KNN-based e-mail classification into folders generating class-balanced datasets.

José A. Gámez, José M. Puerta, Pablo Bermejo, 2008 .

Structural Learning of Bayesian Networks by Using Variable Neighbourhood Search Based on the Space of Orderings

Jose Miguel Puerta, Luis de la Ossa, Juan Ignacio Alonso-Barba, 2009, 2009 Ninth International Conference on Intelligent Systems Design and Applications.

MiniAnDE: A Reduced AnDE Ensemble to Deal with Microarray Data

J. M. Puerta, J. A. Gamez, Pablo Torrijos, 2023, International Conference on Engineering Applications of Neural Networks.

Bayesian Network Classifiers Under the Ensemble Perspective

Jose Miguel Puerta, José A. Gámez, Jacinto Arias, 2018, PGM.

GAODE and HAODE: two proposals based on AODE to deal with continuous variables

Jose Miguel Puerta, José A. Gámez, Ana M. Martínez, 2009, ICML '09.

HODE: Hidden One-Dependence Estimator

Jose Miguel Puerta, José A. Gámez, Ana M. Martínez, 2009, ECSQARU.

Low-complexity heterogeneous architecture for H.264/HEVC video transcoding

A. J. Díaz-Honrubia, P. Cuenca, José Luis Martínez, 2016, Journal of Real-Time Image Processing.