| 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 |
| 2003 | AIME | Finding and Explaining Optimal Treatments. | Concha Bielza, Juan A. Fernndez del Pozo, Peter J. F. Lucas |
| 2003 | SGAI | Optimal Decision Explanation by Extracting Regularity Patterns. | Concha Bielza, Juan A. Fernndez del Pozo, Peter J. F. Lucas |
| 1997 | AISTATS | Markov chain Monte Carlo methods for decision analysis. | Concha Bielza, Peter Mller, David Ros Insua |
| 1997 | AISTATS | A Comparison of Decision Trees, Influence Diagrams and Valuation Networks for Asymmetric Decision Problems. | Concha Bielza, Prakash P. Shenoy |