| 2023 | CEC | Variational Quantum Algorithm Parameter Tuning with Estimation of Distribution Algorithms. | Vicente P. Soloviev, Pedro Larraaga, Concha Bielza |
| 2022 | GECCO | Quantum parametric circuit optimization with estimation of distribution algorithms. | Vicente P. Soloviev, Pedro Larraaga, Concha Bielza |
| 2021 | CEC | Quantum-Inspired Estimation Of Distribution Algorithm To Solve The Travelling Salesman Problem. | Vicente P. Soloviev, Concha Bielza, Pedro Larraaga |
| 2021 | HAIS | Structure Learning of High-Order Dynamic Bayesian Networks via Particle Swarm Optimization with Order Invariant Encoding. | David Quesada, Concha Bielza, Pedro Larraaga |
| 2018 | IDEAL | A Fast Metropolis-Hastings Method for Generating Random Correlation Matrices. | Irene Crdoba, Gherardo Varando, Concha Bielza, Pedro Larraaga |
| 2018 | IDEAL | Multi-dimensional Bayesian Network Classifier Trees. | Santiago Gil-Begue, Pedro Larraaga, Concha Bielza |
| 2017 | ETFA | Architecture for anomaly detection in a laser heating surface process. | Javier Mesonero, Concha Bielza, Pedro Larraaga |
| 2016 | ECAI | Hybrid Gaussian and von Mises Model-Based Clustering. | Sergio Luengo-Sanchez, Concha Bielza, Pedro Larraaga |
| 2015 | ECSQARU | Towards Gaussian Bayesian Network Fusion. | Irene Crdoba-Snchez, Concha Bielza, Pedro Larraaga |
| 2013 | AIME | Semi-supervised Projected Clustering for Classifying GABAergic Interneurons. | Luis Guerra, Ruth Benavides-Piccione, Concha Bielza, Vctor Robles, Javier DeFelipe, Pedro Larraaga |
| 2013 | CBMS | Bayesian networks to answer challenging neuroscience questions. | Pedro Larraaga, Concha Bielza |
| 2013 | GECCO | Towards optimal neuronal wiring through estimation of distribution algorithms. | Laura Anton-Sanchez, Concha Bielza, Pedro Larraaga |
| 2012 | GECCO | Maximizing the number of polychronous groups in spiking networks. | Roberto Santana, Concha Bielza, Pedro Larraaga |
| 2011 | EMO | Multi-objective Optimization with Joint Probabilistic Modeling of Objectives and Variables. | Hossein Karshenas, Roberto Santana, Concha Bielza, Pedro Larraaga |
| 2011 | GECCO | Affinity propagation enhanced by estimation of distribution algorithms. | Roberto Santana, Concha Bielza, Pedro Larraaga |
| 2011 | GECCO | Regularized k-order markov models in EDAs. | Roberto Santana, Hossein Karshenas, Concha Bielza, Pedro Larraaga |
| 2011 | GECCO | Quantitative genetics in multi-objective optimization algorithms: from useful insights to effective methods. | Roberto Santana, Hossein Karshenas, Concha Bielza, Pedro Larraaga |
| 2011 | IJCAI | Bayesian Chain Classifiers for Multidimensional Classification. | Julio H. Zaragoza, Luis Enrique Sucar, Eduardo F. Morales, Concha Bielza, Pedro Larraaga |
| 2011 | ISDA | Predicting the h-index with cost-sensitive naive Bayes. | Alfonso Ibez, Pedro Larraaga, Concha Bielza |
| 2010 | CEC | Bivariate empirical and n-variate Archimedean copulas in estimation of distribution algorithms. | Alfredo Cuesta-Infante, Roberto Santana, Jos Ignacio Hidalgo, Concha Bielza, Pedro Larraaga |
| 2009 | GECCO | Mining probabilistic models learned by EDAs in the optimization of multi-objective problems. | Roberto Santana, Concha Bielza, Jos Antonio Lozano, Pedro Larraaga |
| 2008 | CEC | Component weighting functions for adaptive search with EDAs. | Roberto Santana, Pedro Larraaga, Jos Antonio Lozano |
| 2008 | PPSN | Adding Probabilistic Dependencies to the Search of Protein Side Chain Configurations Using EDAs. | Roberto Santana, Pedro Larraaga, Jos Antonio Lozano |
| 2007 | CEC | Exact Bayesian network learning in estimation of distribution algorithms. | Carlos Echegoyen, Jos Antonio Lozano, Roberto Santana, Pedro Larraaga |
| 2007 | ECSQARU | Discriminative vs. Generative Learning of Bayesian Network Classifiers. | Guzmn Santaf, Jos Antonio Lozano, Pedro Larraaga |
| 2006 | DIS | Information Theory and Classification Error in Probabilistic Classifiers. | Aritz Prez Martnez, Pedro Larraaga, Iaki Inza |
| 2005 | CEC | Interactions and dependencies in estimation of distribution algorithms. | Roberto Santana, Pedro Larraaga, Jos Antonio Lozano |
| 2005 | ECSQARU | Discriminative Learning of Bayesian Network Classifiers via the TM Algorithm. | Guzmn Santaf, Jos Antonio Lozano, Pedro Larraaga |
| 2005 | IWANN | Average Time Complexity of Estimation of Distribution Algorithms. | Cristina Gonzlez, A. Ramrez, Jos Antonio Lozano, Pedro Larraaga |
| 2003 | EPIA | Learning Semi Nave Bayes Structures by Estimation of Distribution Algorithms. | Vctor Robles, Pedro Larraaga, Jos M. Pea, Mara S. Prez, Ernestina Menasalvas Ruiz, Vanessa Herves |
| 2003 | IDA | Interval Estimation Nave Bayes. | Vctor Robles, Pedro Larraaga, Jos M. Pea, Ernestina Menasalvas Ruiz, Mara S. Prez |
| 2003 | IWANN | Analysis of the Univariate Marginal Distribution Algorithm Modeled by Markov Chains. | Cristina Gonzlez, Juan Diego Rodrguez, Jos Antonio Lozano, Pedro Larraaga |
| 2003 | PPAM | Parallel Stochastic Search for Protein Secondary Structure Prediction. | Vctor Robles, Mara S. Prez, Vanessa Herves, Jos M. Pea, Pedro Larraaga |
| 2001 | AIME | Prototype Selection and Feature Subset Selection by Estimation of Distribution Algorithms. A Case Study in the Survival of Cirrhotic Patients Treated with TIPS. | Basilio Sierra, Elena Lazkano, Iaki Inza, Marisa Merino, Pedro Larraaga, Jorge Quiroga |
| 2001 | AISTATS | Geographical clustering of cancer incidence by means of Bayesian networks and conditional Gaussian networks. | Jos M. Pea, I. Izarzugaza, Jos Antonio Lozano, E. Aldasoro, Pedro Larraaga |
| 2000 | UAI | Combinatonal Optimization by Learning and Simulation of Bayesian Networks. | Pedro Larraaga, Ramon Etxeberria, Jos Antonio Lozano, Jos M. Pea |
| 1997 | AIME | Learning Bayesisan Networks by Genetic Algorithms: A Case Study in the Prediction of Survival in Malignant Skin Melanoma. | Pedro Larraaga, Basilio Sierra, Miren J. Gallego, Maria J. Michelena, Juan M. Picaza |
| 1997 | EPIA | Bayesian Networks, Rule Induction and Logistic Regression in the Prediction of the Survival of Women Suffering from Breast Cancer. | Pedro Larraaga, Miren J. Gallego, Basilio Sierra, L. Urkola, Maria J. Michelena |
| 1995 | AISTATS | Structure Learning of Bayesian Networks by Hybrid Genetic Algorithms. | Pedro Larraaga, Roberto H. Murga, Mikel Poza, Cindy M. H. Kuijpers |
| 1993 | ECSQARU | Structure learning approaches in Causal Probalistics Networks. | Pedro Larraaga, Yosu Yurramendi |