| 2009 |
|---|
| 85 | EE | Aritz Pérez,
Pedro Larrañaga,
Iñaki Inza:
Bayesian classifiers based on kernel density estimation: Flexible classifiers.
Int. J. Approx. Reasoning 50(2): 341-362 (2009) |
| 84 | EE | Txomin Romero,
Pedro Larrañaga:
Triangulation of Bayesian networks with recursive estimation of distribution algorithms.
Int. J. Approx. Reasoning 50(3): 472-484 (2009) |
| 83 | EE | Roberto Santana,
Pedro Larrañaga,
José Antonio Lozano:
Research topics in discrete estimation of distribution algorithms based on factorizations.
Memetic Computing 1(1): 35-54 (2009) |
| 2008 |
|---|
| 82 | EE | Roberto Santana,
Pedro Larrañaga,
José Antonio Lozano:
Component weighting functions for adaptive search with EDAs.
IEEE Congress on Evolutionary Computation 2008: 4066-4073 |
| 81 | EE | Roberto Santana,
Pedro Larrañaga,
José Antonio Lozano:
Adding Probabilistic Dependencies to the Search of Protein Side Chain Configurations Using EDAs.
PPSN 2008: 1120-1129 |
| 80 | EE | Roberto Santana,
Pedro Larrañaga,
José Antonio Lozano:
Adaptive Estimation of Distribution Algorithms.
Adaptive and Multilevel Metaheuristics 2008: 177-197 |
| 79 | EE | Carlos Echegoyen,
Roberto Santana,
José Antonio Lozano,
Pedro Larrañaga:
The Impact of Exact Probabilistic Learning Algorithms in EDAs Based on Bayesian Networks.
Linkage in Evolutionary Computation 2008: 109-139 |
| 78 | EE | Dinora Araceli Morales,
Endika Bengoetxea,
Pedro Larrañaga,
Miguel García,
Yosu Franco,
Mónica Fresnada,
Marisa Merino:
Bayesian classification for the selection of in vitro human embryos using morphological and clinical data.
Computer Methods and Programs in Biomedicine 90(2): 104-116 (2008) |
| 77 | EE | Rubén Armañanzas,
Iñaki Inza,
Pedro Larrañaga:
Detecting reliable gene interactions by a hierarchy of Bayesian network classifiers.
Computer Methods and Programs in Biomedicine 91(2): 110-121 (2008) |
| 76 | EE | Roberto Santana,
Pedro Larrañaga,
José Antonio Lozano:
Protein Folding in Simplified Models With Estimation of Distribution Algorithms.
IEEE Trans. Evolutionary Computation 12(4): 418-438 (2008) |
| 75 | EE | Roberto Santana,
Pedro Larrañaga,
José Antonio Lozano:
Combining variable neighborhood search and estimation of distribution algorithms in the protein side chain placement problem.
J. Heuristics 14(5): 519-547 (2008) |
| 74 | EE | Guzmán Santafé,
José Antonio Lozano,
Pedro Larrañaga:
Inference of Population Structure Using Genetic Markers and a Bayesian Model Averaging Approach for Clustering.
Journal of Computational Biology 15(2): 207-220 (2008) |
| 2007 |
|---|
| 73 | EE | Guzmán Santafé,
José Antonio Lozano,
Pedro Larrañaga:
Discriminative vs. Generative Learning of Bayesian Network Classifiers.
ECSQARU 2007: 453-464 |
| 72 | EE | Roberto Santana,
Pedro Larrañaga,
José Antonio Lozano:
The Role of a Priori Information in the Minimization of Contact Potentials by Means of Estimation of Distribution Algorithms.
EvoBIO 2007: 247-257 |
| 71 | EE | Carlos Echegoyen,
José Antonio Lozano,
Roberto Santana,
Pedro Larrañaga:
Exact Bayesian network learning in estimation of distribution algorithms.
IEEE Congress on Evolutionary Computation 2007: 1051-1058 |
| 70 | EE | Roberto Santana,
Pedro Larrañaga,
José Antonio Lozano:
Side chain placement using estimation of distribution algorithms.
Artificial Intelligence in Medicine 39(1): 49-63 (2007) |
| 69 | EE | Yvan Saeys,
Iñaki Inza,
Pedro Larrañaga:
A review of feature selection techniques in bioinformatics.
Bioinformatics 23(19): 2507-2517 (2007) |
| 68 | EE | Borja Calvo,
Núria López-Bigas,
Simon J. Furney,
Pedro Larrañaga,
José Antonio Lozano:
A partially supervised classification approach to dominant and recessive human disease gene prediction.
Computer Methods and Programs in Biomedicine 85(3): 229-237 (2007) |
| 67 | EE | Teresa Miquélez,
Endika Bengoetxea,
Alexander Mendiburu,
Pedro Larrañaga:
Combining Bayesian classifiers and estimation of distribution algorithms for optimization in continuous domains.
Connect. Sci. 19(4): 297-319 (2007) |
| 66 | EE | J. L. Flores,
Iñaki Inza,
Pedro Larrañaga:
Wrapper discretization by means of estimation of distribution algorithms.
Intell. Data Anal. 11(5): 525-545 (2007) |
| 65 | EE | Borja Calvo,
Pedro Larrañaga,
José Antonio Lozano:
Learning Bayesian classifiers from positive and unlabeled examples.
Pattern Recognition Letters 28(16): 2375-2384 (2007) |
| 2006 |
|---|
| 64 | EE | Aritz Pérez Martínez,
Pedro Larrañaga,
Iñaki Inza:
Information Theory and Classification Error in Probabilistic Classifiers.
Discovery Science 2006: 347-351 |
| 63 | EE | Roberto Santana,
Pedro Larrañaga,
José Antonio Lozano:
Mixtures of Kikuchi Approximations.
ECML 2006: 365-376 |
| 62 | EE | Guzmán Santafé,
José Antonio Lozano,
Pedro Larrañaga:
Bayesian Model Averaging of TAN Models for Clustering.
Probabilistic Graphical Models 2006: 271-278 |
| 61 | EE | Teresa Miquélez,
Endika Bengoetxea,
Pedro Larrañaga:
Evolutionary Bayesian Classifier-Based Optimization in Continuous Domains.
SEAL 2006: 529-536 |
| 60 | EE | Pedro Larrañaga,
Borja Calvo,
Roberto Santana,
Concha Bielza,
Josu Galdiano,
Iñaki Inza,
José Antonio Lozano,
Rubén Armañanzas,
Guzmán Santafé,
Aritz Pérez Martínez,
Victor Robles:
Machine learning in bioinformatics.
Briefings in Bioinformatics 7(1): 86-112 (2006) |
| 59 | EE | Aritz Pérez Martínez,
Pedro Larrañaga,
Iñaki Inza:
Supervised classification with conditional Gaussian networks: Increasing the structure complexity from naive Bayes.
Int. J. Approx. Reasoning 43(1): 1-25 (2006) |
| 2005 |
|---|
| 58 | EE | Roberto Santana,
Pedro Larrañaga,
José Antonio Lozano:
Interactions and dependencies in estimation of distribution algorithms.
Congress on Evolutionary Computation 2005: 1418-1425 |
| 57 | EE | Guzmán Santafé,
José Antonio Lozano,
Pedro Larrañaga:
Discriminative Learning of Bayesian Network Classifiers via the TM Algorithm.
ECSQARU 2005: 148-160 |
| 56 | EE | C. González,
A. Ramírez,
José Antonio Lozano,
Pedro Larrañaga:
Average Time Complexity of Estimation of Distribution Algorithms.
IWANN 2005: 42-49 |
| 55 | EE | Pedro Larrañaga,
José Antonio Lozano:
Editorial Introduction Special Issue on Estimation of Distribution Algorithms.
Evolutionary Computation 13(1): (2005) |
| 54 | EE | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga:
Globally Multimodal Problem Optimization Via an Estimation of Distribution Algorithm Based on Unsupervised Learning of Bayesian Networks.
Evolutionary Computation 13(1): 43-66 (2005) |
| 53 | EE | Rosa Blanco,
Iñaki Inza,
Marisa Merino,
Jorge Quiroga,
Pedro Larrañaga:
Feature selection in Bayesian classifiers for the prognosis of survival of cirrhotic patients treated with TIPS.
Journal of Biomedical Informatics 38(5): 376-388 (2005) |
| 52 | EE | Pedro Larrañaga,
José Antonio Lozano,
José Manuel Peña,
Iñaki Inza:
Editorial.
Machine Learning 59(3): 211-212 (2005) |
| 51 | EE | Roberto Marcondes Cesar Junior,
Endika Bengoetxea,
Isabelle Bloch,
Pedro Larrañaga:
Inexact graph matching for model-based recognition: Evaluation and comparison of optimization algorithms.
Pattern Recognition 38(11): 2099-2113 (2005) |
| 2004 |
|---|
| 50 | EE | José M. Peña Sánchez,
Víctor Robles,
Pedro Larrañaga,
Vanessa Herves,
F. Rosales,
María S. Pérez:
GA-EDA: Hybrid Evolutionary Algorithm Using Genetic and Estimation of Distribution Algorithms.
IEA/AIE 2004: 361-371 |
| 49 | EE | Rosa Blanco,
Linda C. van der Gaag,
Iñaki Inza,
Pedro Larrañaga:
Selective Classifiers Can Be Too Restrictive: A Case-Study in Oesophageal Cancer.
ISBMDA 2004: 212-223 |
| 48 | EE | Roberto Santana,
Pedro Larrañaga,
José Antonio Lozano:
Protein Folding in 2-Dimensional Lattices with Estimation of Distribution Algorithms.
ISBMDA 2004: 388-398 |
| 47 | EE | Víctor Robles,
Pedro Larrañaga,
José Manuel Peña,
Ernestina Menasalvas Ruiz,
María S. Pérez,
Vanessa Herves,
Anita Wasilewska:
Bayesian network multi-classifiers for protein secondary structure prediction.
Artificial Intelligence in Medicine 31(2): 117-136 (2004) |
| 46 | EE | Iñaki Inza,
Pedro Larrañaga,
Rosa Blanco,
Antonio J. Cerrolaza:
Filter versus wrapper gene selection approaches in DNA microarray domains.
Artificial Intelligence in Medicine 31(2): 91-103 (2004) |
| 45 | EE | Txomin Romero,
Pedro Larrañaga,
Basilio Sierra:
Learning Bayesian Networks In The Space Of Orderings With Estimation Of Distribution Algorithms.
IJPRAI 18(4): 607-625 (2004) |
| 44 | EE | Rosa Blanco,
Pedro Larrañaga,
Iñaki Inza,
Basilio Sierra:
Gene Selection For Cancer Classification Using Wrapper Approaches.
IJPRAI 18(8): 1373-1390 (2004) |
| 43 | EE | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga:
Unsupervised Learning Of Bayesian Networks Via Estimation Of Distribution Algorithms: An Application To Gene Expression Data Clustering.
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 12(Supplement-1): 63-82 (2004) |
| 2003 |
|---|
| 42 | EE | Víctor Robles,
Pedro Larrañaga,
José M. Peña Sánchez,
Oscar Marbán,
F. Javier Crespo,
María S. Pérez:
Collaborative Filtering Using Interval Estimation Naïve Bayes.
AWIC 2003: 46-53 |
| 41 | EE | Víctor Robles,
Pedro Larrañaga,
José M. Peña Sánchez,
María S. Pérez,
Ernestina Menasalvas Ruiz,
Vanessa Herves:
Learning Semi Naïve Bayes Structures by Estimation of Distribution Algorithms.
EPIA 2003: 244-258 |
| 40 | EE | Víctor Robles,
Pedro Larrañaga,
José M. Peña Sánchez,
Ernestina Menasalvas Ruiz,
María S. Pérez:
Interval Estimation Naïve Bayes.
IDA 2003: 143-154 |
| 39 | EE | C. González,
J. D. Rodríguez,
José Antonio Lozano,
Pedro Larrañaga:
Analysis of the Univariate Marginal Distribution Algorithm Modeled by Markov Chains.
IWANN (1) 2003: 510-517 |
| 38 | EE | Víctor Robles,
María S. Pérez,
Vanessa Herves,
José M. Peña Sánchez,
Pedro Larrañaga:
Parallel Stochastic Search for Protein Secondary Structure Prediction.
PPAM 2003: 1162-1169 |
| 37 | EE | Víctor Robles,
Pedro Larrañaga,
Ernestina Menasalvas Ruiz,
María S. Pérez,
Vanessa Herves:
Improvement of Naïve Bayes Collaborative Filtering Using Interval Estimation.
Web Intelligence 2003: 168-174 |
| 36 | EE | Rosa Blanco,
Iñaki Inza,
Pedro Larrañaga:
Learning Bayesian networks in the space of structures by estimation of distribution algorithms.
Int. J. Intell. Syst. 18(2): 205-220 (2003) |
| 35 | EE | Pedro Larrañaga,
José Antonio Lozano,
Heinz Mühlenbein:
Algoritmos de Estimación de Distribuciones en Problemas de Optimización Combinatoria.
Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial 19: 149-168 (2003) |
| 2002 |
|---|
| 34 | EE | Rosa Blanco,
Iñaki Inza,
Pedro Larrañaga:
Floating Search Methods in Learning Bayesian Networks.
Probabilistic Graphical Models 2002 |
| 33 | EE | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga:
Unsupervised Learning of Bayesian Networks Via Estimation of Distribution Algorithms.
Probabilistic Graphical Models 2002 |
| 32 | EE | Pedro Larrañaga,
José Antonio Lozano:
Synergies between evolutionary computation and probabilistic graphical models.
Int. J. Approx. Reasoning 31(3): 155-156 (2002) |
| 31 | EE | C. González,
José Antonio Lozano,
Pedro Larrañaga:
Mathematical modelling of UMDAc algorithm with tournament selection. Behaviour on linear and quadratic functions.
Int. J. Approx. Reasoning 31(3): 313-340 (2002) |
| 30 | | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga:
Learning Recursive Bayesian Multinets for Data Clustering by Means of Constructive Induction.
Machine Learning 47(1): 63-89 (2002) |
| 29 | EE | Endika Bengoetxea,
Pedro Larrañaga,
Isabelle Bloch,
Aymeric Perchant,
Claudia Boeres:
Inexact graph matching by means of estimation of distribution algorithms.
Pattern Recognition 35(12): 2867-2880 (2002) |
| 2001 |
|---|
| 28 | EE | Basilio Sierra,
Elena Lazkano,
Iñaki Inza,
Marisa Merino,
Pedro Larrañaga,
Jorge Quiroga:
Prototype Selection and Feature Subset Selection by Estimation of Distribution Algorithms. A Case Study in the Survival of Cirrhotic Patients Treated with TIPS.
AIME 2001: 20-29 |
| 27 | EE | Endika Bengoetxea,
Pedro Larrañaga,
Isabelle Bloch,
Aymeric Perchant:
Estimation of Distribution Algorithms: A New Evolutionary Computation Approach for Graph Matching Problems.
EMMCVPR 2001: 454-468 |
| 26 | EE | Basilio Sierra,
Iñaki Inza,
Pedro Larrañaga:
On Applying Supervised Classification Techniques in Medicine.
ISMDA 2001: 14-19 |
| 25 | | Basilio Sierra,
Nicolás Serrano,
Pedro Larrañaga,
Eliseo J. Plasencia,
Iñaki Inza,
Juan José Jiménez,
Pedro Revuelta,
María Luisa Mora:
Using Bayesian networks in the construction of a bi-level multi-classifier. A case study using intensive care unit patients data.
Artificial Intelligence in Medicine 22(3): 233-248 (2001) |
| 24 | | Iñaki Inza,
Marisa Merino,
Pedro Larrañaga,
Jorge Quiroga,
Basilio Sierra,
Marcos Girala:
Feature subset selection by genetic algorithms and estimation of distribution algorithms - A case study in the survival of cirrhotic patients treated with TIPS.
Artificial Intelligence in Medicine 23(2): 187-205 (2001) |
| 23 | EE | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga,
Iñaki Inza:
Dimensionality Reduction in Unsupervised Learning of Conditional Gaussian Networks.
IEEE Trans. Pattern Anal. Mach. Intell. 23(6): 590-603 (2001) |
| 22 | EE | Iñaki Inza,
Pedro Larrañaga,
Basilio Sierra:
Feature subset selection by Bayesian networks: a comparison with genetic and sequential algorithms.
Int. J. Approx. Reasoning 27(2): 143-164 (2001) |
| 21 | EE | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga:
Performance evaluation of compromise conditional Gaussian networks for data clustering.
Int. J. Approx. Reasoning 28(1): 23-50 (2001) |
| 2000 |
|---|
| 20 | EE | Basilio Sierra,
Iñaki Inza,
Pedro Larrañaga:
Medical Bayes Networks.
ISMDA 2000: 4-14 |
| 19 | EE | Iñaki Inza,
Marisa Merino,
Pedro Larrañaga,
Jorge Quiroga,
Basilio Sierra,
Marcos Girala:
Feature Subset Selection Using Probabilistic Tree Structures. A Case Study in the Survival of Cirrhotic Patients Treated with TIPS.
ISMDA 2000: 97-110 |
| 18 | EE | Pedro Larrañaga,
Ramon Etxeberria,
José Antonio Lozano,
José Manuel Peña:
Combinatonal Optimization by Learning and Simulation of Bayesian Networks.
UAI 2000: 343-352 |
| 17 | EE | Iñaki Inza,
Pedro Larrañaga,
Ramon Etxeberria,
Basilio Sierra:
Feature Subset Selection by Bayesian network-based optimization.
Artif. Intell. 123(1-2): 157-184 (2000) |
| 16 | EE | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga:
An improved Bayesian structural EM algorithm for learning Bayesian networks for clustering.
Pattern Recognition Letters 21(8): 779-786 (2000) |
| 1999 |
|---|
| 15 | EE | Basilio Sierra,
Nicolás Serrano,
Pedro Larrañaga,
Eliseo J. Plasencia,
Iñaki Inza,
Juan José Jiménez,
Jose María De la Rosa,
María Luisa Mora:
Machine Learning Inspired Approaches to Combine Standard Medical Measures at an Intensive Care Unit.
AIMDM 1999: 366-371 |
| 14 | | Pedro Larrañaga,
Cindy M. H. Kuijpers,
Roberto H. Murga,
Iñaki Inza,
S. Dizdarevic:
Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators.
Artif. Intell. Rev. 13(2): 129-170 (1999) |
| 13 | EE | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga:
An empirical comparison of four initialization methods for the K-Means algorithm.
Pattern Recognition Letters 20(10): 1027-1040 (1999) |
| 12 | EE | Iñaki Inza,
Pedro Larrañaga,
Basilio Sierra,
Ramon Etxeberria,
José Antonio Lozano,
José Manuel Peña:
Representing the behaviour of supervised classification learning algorithms by Bayesian networks.
Pattern Recognition Letters 20(11-13): 1201-1209 (1999) |
| 11 | EE | José Manuel Peña,
José Antonio Lozano,
Pedro Larrañaga:
Learning Bayesian networks for clustering by means of constructive induction.
Pattern Recognition Letters 20(11-13): 1219-1230 (1999) |
| 10 | EE | José Antonio Lozano,
Pedro Larrañaga:
Applying genetic algorithms to search for the best hierarchical clustering of a dataset.
Pattern Recognition Letters 20(9): 911-918 (1999) |
| 9 | EE | José Antonio Lozano,
Pedro Larrañaga,
Manuel Graña,
F. Xabier Albizuri:
Genetic Algorithms: Bridging the Convergence Gap.
Theor. Comput. Sci. 229(1): 11-22 (1999) |
| 1998 |
|---|
| 8 | | Basilio Sierra,
Pedro Larrañaga:
Predicting survival in malignant skin melanoma using Bayesian networks automatically induced by genetic algorithms. An empirical comparison between different approaches.
Artificial Intelligence in Medicine 14(1-2): 215-230 (1998) |
| 7 | | José Antonio Lozano,
Pedro Larrañaga:
Aplicación de los algoritmos genéticos al problema del clustering jerárquico.
Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial 5: 62-67 (1998) |
| 1997 |
|---|
| 6 | | Pedro Larrañaga,
Basilio Sierra,
Miren J. Gallego,
Maria J. Michelena,
Juan M. Picaza:
Learning Bayesisan Networks by Genetic Algorithms: A Case Study in the Prediction of Survival in Malignant Skin Melanoma.
AIME 1997: 261-272 |
| 5 | | Pedro Larrañaga,
Miren J. Gallego,
Basilio Sierra,
L. Urkola,
Maria J. Michelena:
Bayesian Networks, Rule Induction and Logistic Regression in the Prediction of the Survival of Women Suffering from Breast Cancer.
EPIA 1997: 303-308 |
| 4 | EE | Ramon Etxeberria,
Pedro Larrañaga,
Juan M. Picaza:
Analysis of the behaviour of genetic algorithms when learning Bayesian network structure from data.
Pattern Recognition Letters 18(11-13): 1269-1273 (1997) |
| 1996 |
|---|
| 3 | EE | Pedro Larrañaga,
Mikel Poza,
Yosu Yurramendi,
Roberto H. Murga,
Cindy M. H. Kuijpers:
Structure Learning of Bayesian Networks by Genetic Algorithms: A Performance Analysis of Control Parameters.
IEEE Trans. Pattern Anal. Mach. Intell. 18(9): 912-926 (1996) |
| 1993 |
|---|
| 2 | | Pedro Larrañaga,
Manuel Graña,
Alicia D'Anjou,
Francisco Javier Torrealdea:
Genetic Algorithms Elitist Probabilistic of Degree 1, a generalization of Simulated Annealing.
AI*IA 1993: 208-217 |
| 1 | | Pedro Larrañaga,
Yosu Yurramendi:
Structure learning approaches in Causal Probalistics Networks.
ECSQARU 1993: 227-232 |
