Search the dblp DataBase
Pedro Larrañaga :
[Publications ]
[Author Rank by year ]
[Co-authors ]
[Prefers ]
[Cites ]
[Cited by ]
Publications of Author
Pedro Larrañaga , Manuel Graña , Alicia D'Anjou , Francisco Javier Torrealdea Genetic Algorithms Elitist Probabilistic of Degree 1, a generalization of Simulated Annealing. [Citation Graph (0, 0)][DBLP ] AI*IA, 1993, pp:208-217 [Conf ] 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. [Citation Graph (0, 0)][DBLP ] AIMDM, 1999, pp:366-371 [Conf ] 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. [Citation Graph (0, 0)][DBLP ] AIME, 1997, pp:261-272 [Conf ] 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. [Citation Graph (0, 0)][DBLP ] AIME, 2001, pp:20-29 [Conf ] Víctor Robles , Pedro Larrañaga , José M. Peña Sánchez , Oscar Marbán , F. Javier Crespo , María S. Pérez Collaborative Filtering Using Interval Estimation Naïve Bayes. [Citation Graph (0, 0)][DBLP ] AWIC, 2003, pp:46-53 [Conf ] Aritz Pérez Martínez , Pedro Larrañaga , Iñaki Inza Information Theory and Classification Error in Probabilistic Classifiers. [Citation Graph (0, 0)][DBLP ] Discovery Science, 2006, pp:347-351 [Conf ] Roberto Santana , Pedro Larrañaga , José Antonio Lozano Mixtures of Kikuchi Approximations. [Citation Graph (0, 0)][DBLP ] ECML, 2006, pp:365-376 [Conf ] Pedro Larrañaga , Yosu Yurramendi Structure learning approaches in Causal Probalistics Networks. [Citation Graph (0, 0)][DBLP ] ECSQARU, 1993, pp:227-232 [Conf ] Guzmán Santafé , José Antonio Lozano , Pedro Larrañaga Discriminative Learning of Bayesian Network Classifiers via the TM Algorithm. [Citation Graph (0, 0)][DBLP ] ECSQARU, 2005, pp:148-160 [Conf ] Endika Bengoetxea , Pedro Larrañaga , Isabelle Bloch , Aymeric Perchant Estimation of Distribution Algorithms: A New Evolutionary Computation Approach for Graph Matching Problems. [Citation Graph (0, 0)][DBLP ] EMMCVPR, 2001, pp:454-468 [Conf ] 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. [Citation Graph (0, 0)][DBLP ] EPIA, 1997, pp:303-308 [Conf ] 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. [Citation Graph (0, 0)][DBLP ] EPIA, 2003, pp:244-258 [Conf ] Víctor Robles , Pedro Larrañaga , José M. Peña Sánchez , Ernestina Menasalvas Ruiz , María S. Pérez Interval Estimation Naïve Bayes. [Citation Graph (0, 0)][DBLP ] IDA, 2003, pp:143-154 [Conf ] 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. [Citation Graph (0, 0)][DBLP ] IEA/AIE, 2004, pp:361-371 [Conf ] 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. [Citation Graph (0, 0)][DBLP ] ISMDA, 2000, pp:97-110 [Conf ] Rosa Blanco , Linda C. van der Gaag , Iñaki Inza , Pedro Larrañaga Selective Classifiers Can Be Too Restrictive: A Case-Study in Oesophageal Cancer. [Citation Graph (0, 0)][DBLP ] ISBMDA, 2004, pp:212-223 [Conf ] Basilio Sierra , Iñaki Inza , Pedro Larrañaga On Applying Supervised Classification Techniques in Medicine. [Citation Graph (0, 0)][DBLP ] ISMDA, 2001, pp:14-19 [Conf ] Roberto Santana , Pedro Larrañaga , José Antonio Lozano Protein Folding in 2-Dimensional Lattices with Estimation of Distribution Algorithms. [Citation Graph (0, 0)][DBLP ] ISBMDA, 2004, pp:388-398 [Conf ] Basilio Sierra , Iñaki Inza , Pedro Larrañaga Medical Bayes Networks. [Citation Graph (0, 0)][DBLP ] ISMDA, 2000, pp:4-14 [Conf ] C. González , J. D. Rodríguez , José Antonio Lozano , Pedro Larrañaga Analysis of the Univariate Marginal Distribution Algorithm Modeled by Markov Chains. [Citation Graph (0, 0)][DBLP ] IWANN (1), 2003, pp:510-517 [Conf ] C. González , A. Ramírez , José Antonio Lozano , Pedro Larrañaga Average Time Complexity of Estimation of Distribution Algorithms. [Citation Graph (0, 0)][DBLP ] IWANN, 2005, pp:42-49 [Conf ] Rosa Blanco , Iñaki Inza , Pedro Larrañaga Floating Search Methods in Learning Bayesian Networks. [Citation Graph (0, 0)][DBLP ] Probabilistic Graphical Models, 2002, pp:- [Conf ] José Manuel Peña , José Antonio Lozano , Pedro Larrañaga Unsupervised Learning of Bayesian Networks Via Estimation of Distribution Algorithms. [Citation Graph (0, 0)][DBLP ] Probabilistic Graphical Models, 2002, pp:- [Conf ] Víctor Robles , María S. Pérez , Vanessa Herves , José M. Peña Sánchez , Pedro Larrañaga Parallel Stochastic Search for Protein Secondary Structure Prediction. [Citation Graph (0, 0)][DBLP ] PPAM, 2003, pp:1162-1169 [Conf ] Teresa Miquélez , Endika Bengoetxea , Pedro Larrañaga Evolutionary Bayesian Classifier-Based Optimization in Continuous Domains. [Citation Graph (0, 0)][DBLP ] SEAL, 2006, pp:529-536 [Conf ] Pedro Larrañaga , Ramon Etxeberria , José Antonio Lozano , José Manuel Peña Combinatonal Optimization by Learning and Simulation of Bayesian Networks. [Citation Graph (0, 0)][DBLP ] UAI, 2000, pp:343-352 [Conf ] Víctor Robles , Pedro Larrañaga , Ernestina Menasalvas Ruiz , María S. Pérez , Vanessa Herves Improvement of Naïve Bayes Collaborative Filtering Using Interval Estimation. [Citation Graph (0, 0)][DBLP ] Web Intelligence, 2003, pp:168-174 [Conf ] Pedro Larrañaga , José Antonio Lozano , Heinz Mühlenbein Algoritmos de Estimación de Distribuciones en Problemas de Optimización Combinatoria. [Citation Graph (0, 0)][DBLP ] Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial, 2003, v:19, n:, pp:149-168 [Journal ] José Antonio Lozano , Pedro Larrañaga Aplicación de los algoritmos genéticos al problema del clustering jerárquico. [Citation Graph (0, 0)][DBLP ] Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial, 1998, v:5, n:, pp:62-67 [Journal ] Iñaki Inza , Pedro Larrañaga , Ramon Etxeberria , Basilio Sierra Feature Subset Selection by Bayesian network-based optimization. [Citation Graph (0, 0)][DBLP ] Artif. Intell., 2000, v:123, n:1-2, pp:157-184 [Journal ] 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. [Citation Graph (0, 0)][DBLP ] Artif. Intell. Rev., 1999, v:13, n:2, pp:129-170 [Journal ] Iñaki Inza , Pedro Larrañaga , Rosa Blanco , Antonio J. Cerrolaza Filter versus wrapper gene selection approaches in DNA microarray domains. [Citation Graph (0, 0)][DBLP ] Artificial Intelligence in Medicine, 2004, v:31, n:2, pp:91-103 [Journal ] 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. [Citation Graph (0, 0)][DBLP ] Artificial Intelligence in Medicine, 2001, v:23, n:2, pp:187-205 [Journal ] 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. [Citation Graph (0, 0)][DBLP ] Artificial Intelligence in Medicine, 2004, v:31, n:2, pp:117-136 [Journal ] Basilio Sierra , Pedro Larrañaga Predicting survival in malignant skin melanoma using Bayesian networks automatically induced by genetic algorithms. An empirical comparison between different approaches. [Citation Graph (0, 0)][DBLP ] Artificial Intelligence in Medicine, 1998, v:14, n:1-2, pp:215-230 [Journal ] 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. [Citation Graph (0, 0)][DBLP ] Artificial Intelligence in Medicine, 2001, v:22, n:3, pp:233-248 [Journal ] 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. [Citation Graph (0, 0)][DBLP ] Briefings in Bioinformatics, 2006, v:7, n:1, pp:86-112 [Journal ] 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. [Citation Graph (0, 0)][DBLP ] Evolutionary Computation, 2005, v:13, n:1, pp:43-66 [Journal ] Pedro Larrañaga , José Antonio Lozano Editorial Introduction Special Issue on Estimation of Distribution Algorithms. [Citation Graph (0, 0)][DBLP ] Evolutionary Computation, 2005, v:13, n:1, pp:- [Journal ] C. González , José Antonio Lozano , Pedro Larrañaga Mathematical modelling of UMDAc algorithm with tournament selection. Behaviour on linear and quadratic functions. [Citation Graph (0, 0)][DBLP ] Int. J. Approx. Reasoning, 2002, v:31, n:3, pp:313-340 [Journal ] Iñaki Inza , Pedro Larrañaga , Basilio Sierra Feature subset selection by Bayesian networks: a comparison with genetic and sequential algorithms. [Citation Graph (0, 0)][DBLP ] Int. J. Approx. Reasoning, 2001, v:27, n:2, pp:143-164 [Journal ] Pedro Larrañaga , José Antonio Lozano Synergies between evolutionary computation and probabilistic graphical models. [Citation Graph (0, 0)][DBLP ] Int. J. Approx. Reasoning, 2002, v:31, n:3, pp:155-156 [Journal ] Aritz Pérez Martínez , Pedro Larrañaga , Iñaki Inza Supervised classification with conditional Gaussian networks: Increasing the structure complexity from naive Bayes. [Citation Graph (0, 0)][DBLP ] Int. J. Approx. Reasoning, 2006, v:43, n:1, pp:1-25 [Journal ] José Manuel Peña , José Antonio Lozano , Pedro Larrañaga Performance evaluation of compromise conditional Gaussian networks for data clustering. [Citation Graph (0, 0)][DBLP ] Int. J. Approx. Reasoning, 2001, v:28, n:1, pp:23-50 [Journal ] Rosa Blanco , Iñaki Inza , Pedro Larrañaga Learning Bayesian networks in the space of structures by estimation of distribution algorithms. [Citation Graph (0, 0)][DBLP ] Int. J. Intell. Syst., 2003, v:18, n:2, pp:205-220 [Journal ] Rosa Blanco , Pedro Larrañaga , Iñaki Inza , Basilio Sierra Gene Selection For Cancer Classification Using Wrapper Approaches. [Citation Graph (0, 0)][DBLP ] IJPRAI, 2004, v:18, n:8, pp:1373-1390 [Journal ] Txomin Romero , Pedro Larrañaga , Basilio Sierra Learning Bayesian Networks In The Space Of Orderings With Estimation Of Distribution Algorithms. [Citation Graph (0, 0)][DBLP ] IJPRAI, 2004, v:18, n:4, pp:607-625 [Journal ] 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. [Citation Graph (0, 0)][DBLP ] International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2004, v:12, n:Supplement-1, pp:63-82 [Journal ] 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. [Citation Graph (0, 0)][DBLP ] Journal of Biomedical Informatics, 2005, v:38, n:5, pp:376-388 [Journal ] Pedro Larrañaga , José Antonio Lozano , José Manuel Peña , Iñaki Inza Editorial. [Citation Graph (0, 0)][DBLP ] Machine Learning, 2005, v:59, n:3, pp:211-212 [Journal ] José Manuel Peña , José Antonio Lozano , Pedro Larrañaga Learning Recursive Bayesian Multinets for Data Clustering by Means of Constructive Induction. [Citation Graph (0, 0)][DBLP ] Machine Learning, 2002, v:47, n:1, pp:63-89 [Journal ] 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. [Citation Graph (0, 0)][DBLP ] IEEE Trans. Pattern Anal. Mach. Intell., 1996, v:18, n:9, pp:912-926 [Journal ] José Manuel Peña , José Antonio Lozano , Pedro Larrañaga , Iñaki Inza Dimensionality Reduction in Unsupervised Learning of Conditional Gaussian Networks. [Citation Graph (0, 0)][DBLP ] IEEE Trans. Pattern Anal. Mach. Intell., 2001, v:23, n:6, pp:590-603 [Journal ] Endika Bengoetxea , Pedro Larrañaga , Isabelle Bloch , Aymeric Perchant , Claudia Boeres Inexact graph matching by means of estimation of distribution algorithms. [Citation Graph (0, 0)][DBLP ] Pattern Recognition, 2002, v:35, n:12, pp:2867-2880 [Journal ] Roberto Marcondes Cesar Junior , Endika Bengoetxea , Isabelle Bloch , Pedro Larrañaga Inexact graph matching for model-based recognition: Evaluation and comparison of optimization algorithms. [Citation Graph (0, 0)][DBLP ] Pattern Recognition, 2005, v:38, n:11, pp:2099-2113 [Journal ] Ramon Etxeberria , Pedro Larrañaga , Juan M. Picaza Analysis of the behaviour of genetic algorithms when learning Bayesian network structure from data. [Citation Graph (0, 0)][DBLP ] Pattern Recognition Letters, 1997, v:18, n:11-13, pp:1269-1273 [Journal ] 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. [Citation Graph (0, 0)][DBLP ] Pattern Recognition Letters, 1999, v:20, n:11-13, pp:1201-1209 [Journal ] José Antonio Lozano , Pedro Larrañaga Applying genetic algorithms to search for the best hierarchical clustering of a dataset. [Citation Graph (0, 0)][DBLP ] Pattern Recognition Letters, 1999, v:20, n:9, pp:911-918 [Journal ] José Manuel Peña , José Antonio Lozano , Pedro Larrañaga An improved Bayesian structural EM algorithm for learning Bayesian networks for clustering. [Citation Graph (0, 0)][DBLP ] Pattern Recognition Letters, 2000, v:21, n:8, pp:779-786 [Journal ] José Manuel Peña , José Antonio Lozano , Pedro Larrañaga An empirical comparison of four initialization methods for the K-Means algorithm. [Citation Graph (0, 0)][DBLP ] Pattern Recognition Letters, 1999, v:20, n:10, pp:1027-1040 [Journal ] José Manuel Peña , José Antonio Lozano , Pedro Larrañaga Learning Bayesian networks for clustering by means of constructive induction. [Citation Graph (0, 0)][DBLP ] Pattern Recognition Letters, 1999, v:20, n:11-13, pp:1219-1230 [Journal ] José Antonio Lozano , Pedro Larrañaga , Manuel Graña , F. Xabier Albizuri Genetic Algorithms: Bridging the Convergence Gap. [Citation Graph (0, 0)][DBLP ] Theor. Comput. Sci., 1999, v:229, n:1, pp:11-22 [Journal ] 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. [Citation Graph (0, 0)][DBLP ] Computer Methods and Programs in Biomedicine, 2007, v:85, n:3, pp:229-237 [Journal ] Guzmán Santafé , José Antonio Lozano , Pedro Larrañaga Discriminative vs. Generative Learning of Bayesian Network Classifiers. [Citation Graph (0, 0)][DBLP ] ECSQARU, 2007, pp:453-464 [Conf ] 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. [Citation Graph (0, 0)][DBLP ] EvoBIO, 2007, pp:247-257 [Conf ] Roberto Santana , Pedro Larrañaga , José Antonio Lozano Interactions and dependencies in estimation of distribution algorithms. [Citation Graph (0, 0)][DBLP ] Congress on Evolutionary Computation, 2005, pp:1418-1425 [Conf ] J. L. Flores , Iñaki Inza , Pedro Larrañaga Wrapper discretization by means of estimation of distribution algorithms. [Citation Graph (0, 0)][DBLP ] Intell. Data Anal., 2007, v:11, n:5, pp:525-545 [Journal ] Using Probabilistic Dependencies Improves the Search of Conductance-Based Compartmental Neuron Models. [Citation Graph (, )][DBLP ] Mining probabilistic models learned by EDAs in the optimization of multi-objective problems. [Citation Graph (, )][DBLP ] Probabilistic Graphical Markov Model Learning: An Adaptive Strategy. [Citation Graph (, )][DBLP ] Bayesian Model Averaging of TAN Models for Clustering. [Citation Graph (, )][DBLP ] Adding Probabilistic Dependencies to the Search of Protein Side Chain Configurations Using EDAs. [Citation Graph (, )][DBLP ] Exact Bayesian network learning in estimation of distribution algorithms. [Citation Graph (, )][DBLP ] Component weighting functions for adaptive search with EDAs. [Citation Graph (, )][DBLP ] Side chain placement using estimation of distribution algorithms. [Citation Graph (, )][DBLP ] A review of feature selection techniques in bioinformatics. [Citation Graph (, )][DBLP ] Predicting citation count of Bioinformatics papers within four years of publication. [Citation Graph (, )][DBLP ] Combining Bayesian classifiers and estimation of distribution algorithms for optimization in continuous domains. [Citation Graph (, )][DBLP ] Search in 0.114secs, Finished in 0.117secs