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ORCIDPedro Larrañaga
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- affiliation: Universidad Politécnica de Madrid
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2020 – today
- 2021
[j139]Santiago Gil-Begue
, Concha Bielza, Pedro Larrañaga:
Multi-dimensional Bayesian network classifiers: A survey. Artif. Intell. Rev. 54(1): 519-559 (2021)- [j138]Bojan Mihaljevic, Pedro Larrañaga, Concha Bielza:
Comparing the Electrophysiology and Morphology of Human and Mouse Layer 2/3 Pyramidal Neurons With Bayesian Networks. Frontiers Neuroinformatics 15: 580873 (2021) - [j137]Mario Michiels, Pedro Larrañaga, Concha Bielza:
BayeSuites: An open web framework for massive Bayesian networks focused on neuroscience. Neurocomputing 428: 166-181 (2021) - 2020
- [j136]Irene Córdoba, Concha Bielza, Pedro Larrañaga, Gherardo Varando:
Sparse Cholesky Covariance Parametrization for Recovering Latent Structure in Ordered Data. IEEE Access 8: 154614-154624 (2020) - [j135]Fernando Rodriguez-Sanchez, Pedro Larrañaga, Concha Bielza:
Incremental Learning of Latent Forests. IEEE Access 8: 224420-224432 (2020) - [j134]Javier Diaz-Rozo, Concha Bielza, Pedro Larrañaga:
Machine-tool condition monitoring with Gaussian mixture models-based dynamic probabilistic clustering. Eng. Appl. Artif. Intell. 89: 103434 (2020) - [j133]Irene Córdoba, Gherardo Varando, Concha Bielza, Pedro Larrañaga:
On generating random Gaussian graphical models. Int. J. Approx. Reason. 125: 240-250 (2020) - [i7]Irene Córdoba, Concha Bielza, Pedro Larrañaga, Gherardo Varando:
Sparse Cholesky covariance parametrization for recovering latent structure in ordered data. CoRR abs/2006.01448 (2020) - [i6]Carlos Puerto-Santana, Pedro Larrañaga, Concha Bielza:
Autoregressive Asymmetric Linear Gaussian Hidden Markov Models. CoRR abs/2010.15604 (2020)
2010 – 2019
- 2019
- [j132]Pablo Fernandez-Gonzalez, Concepcion Bielza, Pedro Larrañaga:
Random Forests for Regression as a Weighted Sum of ${k}$ -Potential Nearest Neighbors. IEEE Access 7: 25660-25672 (2019) - [j131]Sergio Luengo-Sanchez, Pedro Larrañaga, Concha Bielza:
A Directional-Linear Bayesian Network and Its Application for Clustering and Simulation of Neural Somas. IEEE Access 7: 69907-69921 (2019) - [j130]Marco Benjumeda, Concha Bielza, Pedro Larrañaga:
Learning tractable Bayesian networks in the space of elimination orders. Artif. Intell. 274: 66-90 (2019) - [j129]Ignacio Leguey, Concha Bielza, Pedro Larrañaga:
Circular Bayesian classifiers using wrapped Cauchy distributions. Data Knowl. Eng. 122: 101-115 (2019) - [j128]Ignacio Leguey, Pedro Larrañaga, Concha Bielza, Shogo Kato:
A circular-linear dependence measure under Johnson-Wehrly distributions and its application in Bayesian networks. Inf. Sci. 486: 240-253 (2019) - [j127]Marco Benjumeda, Sergio Luengo-Sanchez, Pedro Larrañaga, Concha Bielza:
Tractable learning of Bayesian networks from partially observed data. Pattern Recognit. 91: 190-199 (2019) - 2018
- [j126]Bojan Mihaljevic, Pedro Larrañaga, Ruth Benavides-Piccione, Sean Hill, Javier DeFelipe, Concha Bielza:
Towards a supervised classification of neocortical interneuron morphologies. BMC Bioinform. 19(1): 511:1-511:22 (2018) - [j125]Marco Benjumeda, Concha Bielza, Pedro Larrañaga:
Tractability of most probable explanations in multidimensional Bayesian network classifiers. Int. J. Approx. Reason. 93: 74-87 (2018) - [j124]Javier Diaz-Rozo, Concha Bielza, Pedro Larrañaga:
Clustering of Data Streams With Dynamic Gaussian Mixture Models: An IoT Application in Industrial Processes. IEEE Internet Things J. 5(5): 3533-3547 (2018) - [j123]Sergio Luengo-Sanchez, Isabel Fernaud, Concha Bielza, Ruth Benavides-Piccione, Pedro Larrañaga, Javier DeFelipe:
3D morphology-based clustering and simulation of human pyramidal cell dendritic spines. PLoS Comput. Biol. 14(6) (2018) - [j122]Laura Anton-Sanchez, Felix Effenberger, Concha Bielza, Pedro Larrañaga, Hermann Cuntz:
A regularity index for dendrites - local statistics of a neuron's input space. PLoS Comput. Biol. 14(11) (2018) - [j121]Bojan Mihaljevic, Concha Bielza, Pedro Larrañaga:
bnclassify: Learning Bayesian Network Classifiers. R J. 10(2): 455 (2018) - [c75]Irene Córdoba, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato, Concha Bielza, Pedro Larrañaga:
Bayesian Optimization of the PC Algorithm for Learning Gaussian Bayesian Networks. CAEPIA 2018: 44-54 - [c74]Carlos Puerto-Santana, Concha Bielza, Pedro Larrañaga:
Asymmetric Hidden Markov Models with Continuous Variables. CAEPIA 2018: 98-107 - [c73]Irene Córdoba, Gherardo Varando, Concha Bielza, Pedro Larrañaga:
A Fast Metropolis-Hastings Method for Generating Random Correlation Matrices. IDEAL (1) 2018: 117-124 - [c72]Santiago Gil-Begue, Pedro Larrañaga, Concha Bielza:
Multi-dimensional Bayesian Network Classifier Trees. IDEAL (1) 2018: 354-363 - [c71]Irene Córdoba, Gherardo Varando, Concha Bielza, Pedro Larrañaga:
A partial orthogonalization method for simulating covariance and concentration graph matrices. PGM 2018: 61-72 - [c70]Bojan Mihaljevic, Concha Bielza, Pedro Larrañaga:
Learning Bayesian network classifiers with completed partially directed acyclic graphs. PGM 2018: 272-283 - [c69]Fernando Rodriguez-Sanchez, Pedro Larrañaga, Concha Bielza:
Discrete model-based clustering with overlapping subsets of attributes. PGM 2018: 392-403 - [i5]Irene Córdoba-Sánchez, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato, Concha Bielza, Pedro Larrañaga:
Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks. CoRR abs/1806.11015 (2018) - [i4]Gherardo Varando, Concha Bielza, Pedro Larrañaga, Eva Riccomagno:
Markov Property in Generative Classifiers. CoRR abs/1811.04759 (2018) - [i3]Irene Córdoba, Concha Bielza, Pedro Larrañaga:
Towards Gaussian Bayesian Network Fusion. CoRR abs/1812.00262 (2018) - 2017
- [j120]Laura Anton-Sanchez, Concha Bielza, Pedro Larrañaga:
Network design through forests with degree- and role-constrained minimum spanning trees. J. Heuristics 23(1): 31-51 (2017) - [j119]Luis Rodriguez-Lujan, Pedro Larrañaga, Concha Bielza:
Frobenius Norm Regularization for the Multivariate Von Mises Distribution. Int. J. Intell. Syst. 32(2): 153-176 (2017) - [j118]Pablo Fernandez-Gonzalez, Concha Bielza, Pedro Larrañaga:
Univariate and bivariate truncated von Mises distributions. Prog. Artif. Intell. 6(2): 171-180 (2017) - [c68]Javier Mesonero, Concha Bielza, Pedro Larrañaga:
Architecture for anomaly detection in a laser heating surface process. ETFA 2017: 1-4 - 2016
- [j117]Hanen Borchani, Pedro Larrañaga, João Gama, Concha Bielza:
Mining multi-dimensional concept-drifting data streams using Bayesian network classifiers. Intell. Data Anal. 20(2): 257-280 (2016) - [j116]Gherardo Varando, Concha Bielza, Pedro Larrañaga:
Decision functions for chain classifiers based on Bayesian networks for multi-label classification. Int. J. Approx. Reason. 68: 164-178 (2016) - [j115]Alfonso Ibáñez, Rubén Armañanzas, Concha Bielza, Pedro Larrañaga:
Genetic algorithms and Gaussian Bayesian networks to uncover the predictive core set of bibliometric indices. J. Assoc. Inf. Sci. Technol. 67(7): 1703-1721 (2016) - [j114]Laura Anton-Sanchez, Concha Bielza, Ruth Benavides-Piccione, Javier DeFelipe, Pedro Larrañaga:
Dendritic and Axonal Wiring Optimization of Cortical GABAergic Interneurons. Neuroinformatics 14(4): 453-464 (2016) - [j113]Marco Benjumeda, Pedro Larrañaga, Concha Bielza:
Learning Bayesian networks with low inference complexity. Prog. Artif. Intell. 5(1): 15-26 (2016) - [c67]Ignacio Leguey, Concha Bielza, Pedro Larrañaga:
Tree-Structured Bayesian Networks for Wrapped Cauchy Directional Distributions. CAEPIA 2016: 207-216 - [c66]Sergio Luengo-Sanchez, Concha Bielza, Pedro Larrañaga:
Hybrid Gaussian and von Mises Model-Based Clustering. ECAI 2016: 855-862 - [c65]Alberto Ogbechie, Javier Diaz-Rozo, Pedro Larrañaga, Concha Bielza:
Dynamic Bayesian Network-Based Anomaly Detection for In-Process Visual Inspection of Laser Surface Heat Treatment. ML4CPS 2016: 17-24 - [c64]Marco Benjumeda, Concha Bielza, Pedro Larrañaga:
Learning Tractable Multidimensional Bayesian Network Classifiers. Probabilistic Graphical Models 2016: 13-24 - [c63]David Atienza, Concha Bielza, Javier Díaz, Pedro Larrañaga:
Anomaly Detection with a Spatio-Temporal Tracking of the Laser Spot. STAIRS 2016: 137-142 - [i2]Irene Córdoba-Sánchez, Concha Bielza, Pedro Larrañaga:
A review of undirected and acyclic directed Gaussian Markov model selection and estimation. CoRR abs/1606.07282 (2016) - 2015
- [j112]Bojan Mihaljevic, Ruth Benavides-Piccione, Luis Guerra, Javier DeFelipe, Pedro Larrañaga, Concha Bielza:
Classifying GABAergic interneurons with semi-supervised projected model-based clustering. Artif. Intell. Medicine 65(1): 49-59 (2015) - [j111]Hossein Karshenas, Concha Bielza, Pedro Larrañaga:
Interval-based ranking in noisy evolutionary multi-objective optimization. Comput. Optim. Appl. 61(2): 517-555 (2015) - [j110]Gherardo Varando, Pedro L. López-Cruz, Thomas D. Nielsen, Pedro Larrañaga, Concha Bielza:
Conditional Density Approximations with Mixtures of Polynomials. Int. J. Intell. Syst. 30(3): 236-264 (2015) - [j109]Gherardo Varando, Concha Bielza, Pedro Larrañaga:
Decision boundary for discrete Bayesian network classifiers. J. Mach. Learn. Res. 16: 2725-2749 (2015) - [j108]Bojan Mihaljevic, Ruth Benavides-Piccione, Concha Bielza, Javier DeFelipe, Pedro Larrañaga:
Bayesian Network Classifiers for Categorizing Cortical GABAergic Interneurons. Neuroinformatics 13(2): 193-208 (2015) - [j107]Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga:
Directional naive Bayes classifiers. Pattern Anal. Appl. 18(2): 225-246 (2015) - [j106]Hanen Borchani, Gherardo Varando, Concha Bielza, Pedro Larrañaga:
A survey on multi-output regression. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 5(5): 216-233 (2015) - [c62]Luis Rodriguez-Lujan, Concha Bielza, Pedro Larrañaga:
Regularized Multivariate von Mises Distribution. CAEPIA 2015: 25-35 - [c61]Irene Córdoba-Sánchez, Concha Bielza, Pedro Larrañaga:
Towards Gaussian Bayesian Network Fusion. ECSQARU 2015: 519-528 - [c60]Javier Díaz, Concha Bielza, Jose L. Ocaña, Pedro Larrañaga:
Development of a Cyber-Physical System based on selective Gaussian naïve Bayes model for a self-predict laser surface heat treatment process control. ML4CPS 2015: 1-8 - 2014
- [j105]Concha Bielza, Pedro Larrañaga:
Discrete Bayesian Network Classifiers: A Survey. ACM Comput. Surv. 47(1): 5:1-5:43 (2014) - [j104]Luis Guerra, Concha Bielza, Víctor Robles, Pedro Larrañaga:
Semi-supervised projected model-based clustering. Data Min. Knowl. Discov. 28(4): 882-917 (2014) - [j103]Concha Bielza, Pedro Larrañaga:
Bayesian networks in neuroscience: a survey. Frontiers Comput. Neurosci. 8: 131 (2014) - [j102]Bojan Mihaljevic, Concha Bielza, Ruth Benavides-Piccione, Javier DeFelipe, Pedro Larrañaga:
Multi-dimensional classification of GABAergic interneurons with Bayesian network-modeled label uncertainty. Frontiers Comput. Neurosci. 8: 150 (2014) - [j101]Pedro L. López-Cruz, Pedro Larrañaga, Javier DeFelipe, Concha Bielza:
Bayesian network modeling of the consensus between experts: An application to neuron classification. Int. J. Approx. Reason. 55(1): 3-22 (2014) - [j100]Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga:
Learning mixtures of polynomials of multidimensional probability densities from data using B-spline interpolation. Int. J. Approx. Reason. 55(4): 989-1010 (2014) - [j99]Alfonso Ibáñez, Concha Bielza, Pedro Larrañaga:
Cost-sensitive selective naive Bayes classifiers for predicting the increase of the h-index for scientific journals. Neurocomputing 135: 42-52 (2014) - [j98]Luis Enrique Sucar, Concha Bielza, Eduardo F. Morales, Pablo Hernandez-Leal, Julio H. Zaragoza, Pedro Larrañaga:
Multi-label classification with Bayesian network-based chain classifiers. Pattern Recognit. Lett. 41: 14-22 (2014) - [j97]Hossein Karshenas, Roberto Santana, Concha Bielza, Pedro Larrañaga:
Multiobjective Estimation of Distribution Algorithm Based on Joint Modeling of Objectives and Variables. IEEE Trans. Evol. Comput. 18(4): 519-542 (2014) - [j96]Jesse Read, Concha Bielza, Pedro Larrañaga:
Multi-Dimensional Classification with Super-Classes. IEEE Trans. Knowl. Data Eng. 26(7): 1720-1733 (2014) - [c59]Gherardo Varando, Concha Bielza, Pedro Larrañaga:
Expressive Power of Binary Relevance and Chain Classifiers Based on Bayesian Networks for Multi-label Classification. Probabilistic Graphical Models 2014: 519-534 - 2013
- [j95]Hanen Borchani, Concha Bielza, Carlos Toro, Pedro Larrañaga:
Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers. Artif. Intell. Medicine 57(3): 219-229 (2013) - [j94]Rubén Armañanzas, Concha Bielza, Kallol Ray Chaudhuri, Pablo Martínez-Martín, Pedro Larrañaga:
Unveiling relevant non-motor Parkinson's disease severity symptoms using a machine learning approach. Artif. Intell. Medicine 58(3): 195-202 (2013) - [j93]Hossein Karshenas, Roberto Santana, Concha Bielza, Pedro Larrañaga:
Regularized continuous estimation of distribution algorithms. Appl. Soft Comput. 13(5): 2412-2432 (2013) - [j92]Jose Luis Flores, Iñaki Inza, Pedro Larrañaga, Borja Calvo:
A new measure for gene expression biclustering based on non-parametric correlation. Comput. Methods Programs Biomed. 112(3): 367-397 (2013) - [j91]Diego Vidaurre, Concha Bielza, Pedro Larrañaga:
Sparse regularized local regression. Comput. Stat. Data Anal. 62: 122-135 (2013) - [j90]Diego Vidaurre, Concha Bielza, Pedro Larrañaga:
An L1-Regularized naïVE Bayes-Inspired Classifier for Discarding Redundant and Irrelevant Predictors. Int. J. Artif. Intell. Tools 22(4) (2013) - [j89]Roberto Santana, Rubén Armañanzas, Concha Bielza, Pedro Larrañaga:
Network measures for information extraction in evolutionary algorithms. Int. J. Comput. Intell. Syst. 6(6): 1163-1188 (2013) - [j88]Diego Vidaurre, Concha Bielza, Pedro Larrañaga:
Classification of neural signals from sparse autoregressive features. Neurocomputing 111: 21-26 (2013) - [j87]Miguel García-Torres, Rubén Armañanzas, Concha Bielza, Pedro Larrañaga:
Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data. Inf. Sci. 222: 229-246 (2013) - [j86]Pedro Larrañaga, Hossein Karshenas, Concha Bielza, Roberto Santana:
A review on evolutionary algorithms in Bayesian network learning and inference tasks. Inf. Sci. 233: 109-125 (2013) - [j85]Concha Bielza, Juan A. Fernández del Pozo, Pedro Larrañaga:
Parameter Control of Genetic Algorithms by Learning and Simulation of Bayesian Networks - A Case Study for the Optimal Ordering of Tables. J. Comput. Sci. Technol. 28(4): 720-731 (2013) - [j84]Diego Vidaurre, Marcel A. J. van Gerven, Concha Bielza, Pedro Larrañaga, Tom Heskes:
Bayesian Sparse Partial Least Squares. Neural Comput. 25(12): 3318-3339 (2013) - [j83]Alfonso Ibáñez, Concha Bielza, Pedro Larrañaga:
Relationship among research collaboration, number of documents and number of citations: a case study in Spanish computer science production in 2000-2009. Scientometrics 95(2): 689-716 (2013) - [j82]Alfonso Ibáñez, Pedro Larrañaga, Concha Bielza:
Cluster methods for assessing research performance: exploring Spanish computer science. Scientometrics 97(3): 571-600 (2013) - [c58]Luis Guerra, Ruth Benavides-Piccione, Concha Bielza, Víctor Robles, Javier DeFelipe, Pedro Larrañaga:
Semi-supervised Projected Clustering for Classifying GABAergic Interneurons. AIME 2013: 156-165 - [c57]Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga:
Learning Conditional Linear Gaussian Classifiers with Probabilistic Class Labels. CAEPIA 2013: 139-148 - [c56]Bojan Mihaljevic, Pedro Larrañaga, Concha Bielza:
Augmented Semi-naive Bayes Classifier. CAEPIA 2013: 159-167 - [c55]Pedro L. López-Cruz, Thomas D. Nielsen, Concha Bielza, Pedro Larrañaga:
Learning Mixtures of Polynomials of Conditional Densities from Data. CAEPIA 2013: 363-372 - [c54]Pedro Larrañaga, Concha Bielza:
Bayesian networks to answer challenging neuroscience questions. CBMS 2013: 2 - [c53]Laura Anton-Sanchez, Concha Bielza, Pedro Larrañaga:
Towards optimal neuronal wiring through estimation of distribution algorithms. GECCO (Companion) 2013: 1647-1650 - [i1]Pedro Larrañaga, Ramon Etxeberria, José Antonio Lozano, José M. Peña:
Combinatorial Optimization by Learning and Simulation of Bayesian Networks. CoRR abs/1301.3871 (2013) - 2012
- [j81]Roberto Santana, Concha Bielza, Pedro Larrañaga:
Regularized logistic regression and multiobjective variable selection for classifying MEG data. Biol. Cybern. 106(6-7): 389-405 (2012) - [j80]Rubén Armañanzas, Pedro Larrañaga, Concha Bielza:
Ensemble transcript interaction networks: A case study on Alzheimer's disease. Comput. Methods Programs Biomed. 108(1): 442-450 (2012) - [j79]Diego Vidaurre, Concha Bielza, Pedro Larrañaga:
Lazy lasso for local regression. Comput. Stat. 27(3): 531-550 (2012) - [j78]Pedro Larrañaga, Hossein Karshenas, Concha Bielza, Roberto Santana:
A review on probabilistic graphical models in evolutionary computation. J. Heuristics 18(5): 795-819 (2012) - [j77]Luis Guerra, Víctor Robles, Concha Bielza, Pedro Larrañaga:
A comparison of clustering quality indices using outliers and noise. Intell. Data Anal. 16(4): 703-715 (2012) - [j76]Hanen Borchani, Concha Bielza, Pablo Martínez-Martín, Pedro Larrañaga:
Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: An application to predict the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39). J. Biomed. Informatics 45(6): 1175-1184 (2012) - [j75]Borja Calvo, Iñaki Inza, Pedro Larrañaga, José Antonio Lozano:
Wrapper positive Bayesian network classifiers. Knowl. Inf. Syst. 33(3): 631-654 (2012) - [j74]Diego Vidaurre, Concha Bielza, Pedro Larrañaga:
Forward stagewise naïve Bayes. Prog. Artif. Intell. 1(1): 57-69 (2012) - [c52]Roberto Santana, Concha Bielza, Pedro Larrañaga:
Maximizing the number of polychronous groups in spiking networks. GECCO (Companion) 2012: 1499-1500 - 2011
- [j73]Pedro Larrañaga, Serafín Moral:
Probabilistic graphical models in artificial intelligence. Appl. Soft Comput. 11(2): 1511-1528 (2011) - [j72]Concha Bielza, Víctor Robles, Pedro Larrañaga:
Regularized logistic regression without a penalty term: An application to cancer classification with microarray data. Expert Syst. Appl. 38(5): 5110-5118 (2011) - [j71]Endika Bengoetxea, Pedro Larrañaga, Concha Bielza, Juan A. Fernández del Pozo:
Optimal row and column ordering to improve table interpretation using estimation of distribution algorithms. J. Heuristics 17(5): 567-588 (2011) - [j70]Hanen Borchani, Pedro Larrañaga, Concha Bielza:
Classifying evolving data streams with partially labeled data. Intell. Data Anal. 15(5): 655-670 (2011) - [j69]Concha Bielza, Guangdi Li, Pedro Larrañaga:
Multi-dimensional classification with Bayesian networks. Int. J. Approx. Reason. 52(6): 705-727 (2011) - [j68]Roberto Santana, Concha Bielza, Pedro Larrañaga:
Optimizing Brain Networks Topologies Using Multi-objective Evolutionary Computation. Neuroinformatics 9(1): 3-19 (2011) - [j67]Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga, Ruth Benavides-Piccione, Javier DeFelipe:
Models and Simulation of 3D Neuronal Dendritic Trees Using Bayesian Networks. Neuroinformatics 9(4): 347-369 (2011) - [j66]Alfonso Ibáñez, Pedro Larrañaga, Concha Bielza:
Using Bayesian networks to discover relationships between bibliometric indices. A case study of computer science and artificial intelligence journals. Scientometrics 89(2): 523-551 (2011) - [j65]Rubén Armañanzas, Yvan Saeys, Iñaki Inza, Miguel García-Torres, Concha Bielza, Yves Van de Peer, Pedro Larrañaga:
Peakbin Selection in Mass Spectrometry Data Using a Consensus Approach with Estimation of Distribution Algorithms. IEEE ACM Trans. Comput. Biol. Bioinform. 8(3): 760-774 (2011) - [c51]Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga:
The von Mises Naive Bayes Classifier for Angular Data. CAEPIA 2011: 145-154 - [c50]Hossein Karshenas, Roberto Santana, Concha Bielza, Pedro Larrañaga:
Multi-objective Optimization with Joint Probabilistic Modeling of Objectives and Variables. EMO 2011: 298-312 - [c49]Roberto Santana, Hossein Karshenas, Concha Bielza, Pedro Larrañaga:
Quantitative genetics in multi-objective optimization algorithms: from useful insights to effective methods. GECCO (Companion) 2011: 91-92 - [c48]Roberto Santana, Concha Bielza, Pedro Larrañaga:
Affinity propagation enhanced by estimation of distribution algorithms. GECCO 2011: 331-338 - [c47]Roberto Santana, Hossein Karshenas, Concha Bielza, Pedro Larrañaga:
Regularized k-order markov models in EDAs. GECCO 2011: 593-600 - [c46]Julio H. Zaragoza, Luis Enrique Sucar, Eduardo F. Morales, Concha Bielza, Pedro Larrañaga:
Bayesian Chain Classifiers for Multidimensional Classification. IJCAI 2011: 2192-2197 - [c45]Alfonso Ibáñez, Pedro Larrañaga, Concha Bielza:
Predicting the h-index with cost-sensitive naive Bayes. ISDA 2011: 599-604 - 2010
- [j64]Roberto Santana, Pedro Larrañaga, José Antonio Lozano:
Learning Factorizations in Estimation of Distribution Algorithms Using Affinity Propagation. Evol. Comput. 18(4): 515-546 (2010) - [j63]Concha Bielza, Juan A. Fernández del Pozo, Pedro Larrañaga, Endika Bengoetxea:
Multidimensional statistical analysis of the parameterization of a genetic algorithm for the optimal ordering of tables. Expert Syst. Appl. 37(1): 804-815 (2010) - [j62]