SELECTED PUBLICATIONS

For a complete list of publications, consult the publication list at the of group's web page.

EDITED BOOKS

Jose A. Lozano, Pedro Larrañaga, Iñaki Inza and Endika Bengoetxea (Editors, 2006) Towards a New Evolutionary Computation. Advances on Estimation of Distribution Algorithms. Springer
Pedro Larrañaga and Jose A. Lozano (Editors, 2002) Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation. Kluwer Academic Publishers

EDITED PROCEEDINGS

E. Corchado, J.A. Lozano, H. Quitan, H. Yin (2014) Intelligent Data Engineering and Automated Learning, IDEAL 2014. Lectures Notes in Computer Science 8669, Springer-Verlag.
C. Blum, E. Alba, J.A. Lozano, et al. (2013) Genetic and Evolutionary Computation Conference, GECCO 2013. ACM 2013.
T. Soule, J.H. Moore, J.A. Lozano, et al. (2012) Genetic and Evolutionary Computation Conference, GECCO 2012. ACM 2012.
J.A. Lozano, J.A. Gamez, J.A. Moreno (2011) Advances in Artificial Intelligence. Lectures Notes in Computer Science 7023, Springer-Verlag.
N. Krasnogor, P. L. Lanzi, J.A. Lozano et al. (2011) Genetic and Evolutionary Computation Conference, GECCO 2011. ACM 2011.
X. Yao, E. Burke, J.A. Lozano, J. Smith, J.J. Merelo-Guervós, J.A. Bullinaria, J. Rowe, P. Tino, A. Kabán and H.-P Schwefel (2004) Parallel Problem Solving from Nature-PPSN VIII. Lecture Notes in Computer Science, Vol. 3242. Springer-Verlag
P. Larrañaga, J.A. Lozano, J.M. Peña and I.Inza (2003) Proceedings of the ECML/PKDD - 2003 Workshop on Probabilistic Graphical Models for Classification. Ruder Boskovic Institute

EDITED SPECIAL ISSUES

Jose A. Lozano, Qingfu Zhang and Pedro Larrañaga (Guest editors, 2009) Special Issue on Evolutionary Algorithms Based on Probabilistic Models IEEE Transaction on Evolutionary Computation. 13(6)
P. Larrañaga, J.A. Lozano, J.M. Peña and I.Inza (Guest editors, 2005) Special Issue on Probabilistic Graphical Models for Classification, Machine Learning, 59(3)
P. Larrañaga and J.A. Lozano (Guest editors, 2005) Special Issue on Estimation of Distribution Algorithms, Evolutionary Computation, 13(1)
P. Larrañaga and J.A. Lozano (2002) Special Issue in Synergies Between Probabilistic Graphical Models and Evolutionary Computation, International Journal of Approximate Reasoning, 31

REFEREED INTERNATIONAL JOURNALS

J. Ortigosa-Hernández, I. Inza, J.A. Lozano (2015) Semi-supervised Multi-class Classification Problems with Scarcity of Labelled Data: A Theoretical Study. IEEE Trans. on Neural Networks and Learning Systems. Accepted.
C. Blum, P. Pinacho, M. López-Ibáñez, J.A. Lozano (2015) Construct, Merge, Solve & Adapt: A New General Algorithm For Combinatorial Optimization. Computers and Operations Research. Accepted.
J. Hernández-González, I. Inza, J.A. Lozano (2015) Weak supervision and other non-standard classification problems: a taxonomy. Pattern Recognition Letters. Accepted.
J. Luo, L. Jiao, J.A. Lozano (2015) A Sparse Spectral Clustering Framework via Multi-Objective Evolutionary Algorithm. IEEE Trans. On Evolutionary Computation. Accepted.
U. Mori, A. Mendiburu, J.A. Lozano (2015) Similarity Measure Selection for Clustering Time Series Databases. IEEE Transaction on Knowledge and Data Engineering. Accepted
L. Hernando, A. Mendiburu and J.A. Lozano (2015) A Tunable Generator of Instances of Permutation-based Combinatorial Optimization Problems. IEEE Trans. On Evolutionary Computation. Accepted.
E. Irurozki, B. Calvo, J.A. Lozano(2015) PerMallows: An R Package for Mallows and Generalized Mallows Models. Journal of Statistical Software. Accepted.
J. Wang, K. Tang, J.A. Lozano, X. Yao (2015) Estimation of Distribution Algorithm with Stochastic Local Search for Uncertain Capacitated Arc Routing Problems. EEE Trans. On Evolutionary Computation. Accepted.
R. Santana, A. Mendiburu, J.A. Lozano (2015) A review of message passing algorithms in estimation of distribution algorithms. Natural Computing. Accepted.
X. Liang, H. Chen, J.A. Lozano (2015) A Boltzmann-based Estimation of Distribution Algorithm for Scheduling a General Resource Model. IEEE Trans. On Evolutionary Computation. Accepted.
J.A. Pascual, T. Lorido-Botran, J. Miguel-Alonso, J.A. Lozano (2015) Towards a Greener Cloud Infrastructure Management using Optimized Placement Policies. Journal of Grid Computing. Accepted.
P. Yang, K. Tang, J.A. Lozano, X. Cao (2015) Path Planning for Single Unmanned Aerial Vehicle by Separately Evolving Waypoints. IEEE Transactions on Robotics, 31(5), 1130-1146.
G. Santafé, I. Inza, J.A. Lozano (2015) Dealing with the evaluation of supervised classification algorithms. Artificial Intelligence Review, 44(4), 467- 508.
C. Echegoyen, R. Santana, A. Mendiburu, J.A. Lozano (2015) Comprehensive Characterization of the Behaviors of Estimation of Distribution Algorithms. Theoretical Computer Science, 598, 64-86.
J. Ceberio, E. Irurozki, A. Mendiburu, J.A. Lozano (2015) A Review of Distances for the Mallows and Generalized Mallows Estimation of Distribution Algorithms. Computational Optimization and Applications, 6(2), 545-564.
R. Santana, A. Mendiburu, J.A. Lozano (2015) Multi-view classification of psychiatric conditions based on saccades. Applied Soft Computing, 31, 308-316.
C. Blum, J.A. Lozano, P. Pinacho (2015) An Artificial Bioindicator System for Network Intrusion Detection Artificial Life, 21(2), 93-118.
Z. Wang, J.-H. Sul, S. Snir, J.A. Lozano, E. Eskin (2015) Gene-Gene Interactions Detection Using A Two-stage Model. Journal of Computational Biology, 22(6), 563-576.
J.A. Fernandes, X. Irigoien, J.A. Lozano, I, Inza, N. Goikoetxea, A. Pérez (2015) Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species. Ecological Informatics, 25, 35-42.
J.A. Pascual, J. Miguel-Alonso, J.A. Lozano (2015) Locality-aware Policies to Improve Job Scheduling in Supercomputers. Journal of Supercomputing, 71(3), 966-994.
C. Blum, J.A. Lozano, P. Pinacho (2015) Mathematical Programming Strategies for Solving the Minimum Common String Partition Problem. European Journal of Operational Research, 242(3), 769-777.
J. Ceberio. E. Irurozki, A. Mendiburu,J.A. Lozano (2015) The Linear Ordering Problem Revisited. European Journal of Operational Research, 241(3), 686-696.
J. Hernández-González, I. Inza, J.A. Lozano (2015) Multi-dimensional learning from crowds: usefulness and application of expertise detection. International Journal of Intelligent Systems, 30(3), 326-354.
U. Mori, A. Mendiburu, J.A. Lozano (2015) A Review of Travel Time Estimation and Prediction for Advanced Traveler Information Systems. Transportmetrica A: Transport Science, 11(2), 119-157.
T. Lorido-Botran, J. Miguel-Alonso, J.A. Lozano(2014) A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments Journal of Grid Computing, 12(4), 559-592.
P. Rozas-Larraondo, I. Inza, J.A. Lozano(2014) A Method for Wind Speed Forecasting in Airports Based on Non-Parametric Regression. Weather and Forecasting, 29(6), 1332-1342.
J.A. Pascual, J. Miguel-Alonso, J.A. Lozano (2014) A fast implementation of the first fit contiguous partitioning strategy for cubic topologies. Concurrency and Computation: Practice and Experience, 26(17), 2792-2810.
J.A. Pascual, J. Miguel-Alonso, J.A. Lozano(2014) Application-aware metrics for partition selection in cube-shaped topologies. Parallel Computing, 40(5-6), 129-139.
J. Ceberio, E. Irurozki, A. Mendiburu, J.A. Lozano(2014) A Distance-based Ranking Model Estimation of Distribution Algorithm for the Flowshop Scheduling Problem. IEEE Transactions on Evolutionary Computation, 18(2), 286-300.
R. Sagarna, A. Mendiburu, I. Inza, J.A. Lozano (2014) Assisting in search heuristics selection through multidimensional supervised classification: A case study on software testing. Information Sciences, 258, 122-139.
J. Hernández, I. Inza, J.A. Lozano (2013) Learning Bayesian network classifiers from label proportions. Pattern Recognition, 46(12), 3425-3440.
L. Hernando, A. Mendiburu, J.A. Lozano (2013) An evaluation of methods for estimating the number of local optima in combinatorial optimization problems. Evolutionary Computation, 21(4), 625-58.
D. Berrar, J.A. Lozano (2013) Significance tests or confidence intervals: which are preferable for the comparison of classifiers? Journal of Experimental & Theoretical Artificial Intelligence, 25(2), 189-206.
C. Echegoyen, A. Mendiburu, R. Santana, J.A. Lozano (2013) On the Taxonomy of Optimization Problems under Estimation of Distribution Algorithms. Evolutionary Computation, 21(3), 471-495.
J.A. Fernandes,J.A. Lozano, I. Inza, X. Irigoien, A. Pérez, J.D. Rodríguez (2013) Supervised pre-processing approaches in multiple class variables classification for fish recruitment forecasting. Environmental Modelling & Software, 40, 245-254.
J.D. Rodríguez, A. Pérez, J.A. Lozano (2013) A General Framework for the Statistical Analysis of the Sources of Variance for classification Error Estimators. Pattern Recognition, 46(3), 855-864.
J.D. Rodríguez, A. Pérez, D. Arteta, D. Tejedor, J.A. Lozano (2012) Using Multi-Dimensional Bayesian Network Classifiers to Assist the Treatment of Multiple Sclerosis. IEEE Transactions on Systems, Man, and Cybernetics{Part C: Applications and Reviews, 42(6), 1705-1715.
B. Calvo, I. Inza, P. Larrañaga, J.A. Lozano (2012) Wrapper positive Bayesian network classi ers. Knowledge and Information Systems, 33(3), 631-654.
J. Ortigosa-Hernández, J.D. Rodríguez, L. Alzate, M. Lucania I. Inza, J.A. Lozano (2012) Approaching Sentiment Analysis by using semi-supervised learning of multi-dimensional classifiers. Special Issue in Data Mining Applicacions and Case Studies, Neurocomputing. 92, 98-115.
S. Shakya, R. Santana, J. A. Lozano(2012) A Markovianity based Optimisation Algorithm. Genetic Programming and Evolvable Machines. 13(2), 159-195.
J. Ceberio, E. Irurozki, A. Mendiburu, J.A. Lozano. (2012) A review on Estimation of Distribution Algorithms in Permutation-based Combinatorial Optimization Problems. Progress in Artificial Intelligence. Springer. 1(1), 103-117.
I. Ibarbia, A. Mendiburu, M. Santos, J. A. Lozano. An interactive optimization approach to a real-world oceanographic campaign planning problem. Applied Intelligence.36(3), 721-734.
C. Echegoyen, A. Mendiburu, R. Santana and J.A. Lozano (2012) Towards understanding EDAs based on Bayesian networks through a quantitative analysis. IEEE Transactions on Evolutionary Computation. 16(2) 173-189.
E. Irurozki, B.Calvo, J.A. Lozano (2011) A Preprocessing Procedure for Haplotype Inference by Pure Parsimony. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB). 8(5) 1183-95. 2011
J. A. Pascual, J. Miguel-Alonso, J. A. Lozano (2011) Optimization-based mapping framework for parallel applications. Journal of Parallel and Distributed Computing, 71(10):1377-1387, 2011.
E. Kostem, J.A. Lozano, E. Eskin (2011) Increasing power of genome-wide association studies by collecting additional single-nucleotide polymorphisms. Genetics. 188(2), 449-60.
R. Santana, A. Mendiburu, N. Zaitlen, E. Eskin, J.A. Lozano.(2010) Multi-marker tagging SNP selection using estimation of distribution algorithms (2010) Artificial Intelligence in Medicine. 50, 193-201.
R. Santana, C. Bielza, P. Larrañaga, J. A. Lozano, C. Echegoyen, A. Mendiburu, R. Armañanzas, S. Shakya (2010). MATEDA: A Matlab package for the implementation and analysis of Estimation of distribution algorithms. Journal of statistical software. American Statistical Association. 35(7), 1-30.
R. Santana, P. Larrañaga, J. A. Lozano (2010) Learning factorizations in estimation of distribution algorithms using affinity propagation. Evolutionary Computation. 18(4), 515-546.
J. D. Rodríguez, A. Pérez, J. A. Lozano (2010) Sensitivity Analysis of k-fold cross-validation in prediction error estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 32 (3), pp. 569--574
J.A. Lozano, Q. Zhang, P. Larrañaga (2009) Guest Editorial: Special Issue on Evolutionary Algorithms Based on Probabilistic Models IEEE Transaction on Evolutionary Computation. 13(6), 1197-1198.
J. A. Fernandes, X. Irigoien, N. Goikoetxea, J. A. Lozano, I. Inza, A. Perez, A. Bode (2009). Fish recruitment prediction, using robust supervised classification methods. Ecological Modelling. , 221(2): 338-352.
D. Otaegui, S. Baranzini, R. Armañanzas, B. Calvo, M. Muñoz-Culla, P. Khankhanian, I. Inza, J. A. Lozano, A. Asensio, T. Castillo-Triviño, J. Olsacoaga, A. López de Munain. Differential microRNA expression in PBMC from multiple sclerosis patients (2009) PLoS ONE. 4(7), e6309.
B. Calvo, P. Larrañaga, J.A. Lozano (2009) Feature subset selection from positive and unlabelled examples. Pattern Recognition Letters, 30, 1027-1036.
J. A. Fernandes, X. Irigoyen, J. A. Lozano, I. Inza (2009) Optimizing the number of classes in automated zooplankton classification. Journal of Plankton Research, 31(1), 19-29.
R. Armañanzas, I. Inza, R. Santana, Y. Saeys, J. L. Flores, J.A. Lozano, Y. Van de Peer, R. Blanco, V. Robles, C. Bielza, P. Larrañaga (2008). A review of estimation of distribution algorithms in bioinformatics. BioData Mining, 1:6.
R. Santana, P. Larrañaga, J.A. Lozano (2008) Research topics in discrete estimation of distribution algorithms. Memetic Computing, 1(1), 35-54.
S. J. Furney, B. Calvo, P. Larrañaga, J. A. Lozano, N. López-Bigas (2008) Prioritization of candidate cancer genes - an aid to oncogenomic studies. Nucleic Acids Research, 36(18), e115.
G. Santafé, J. A. Lozano, P. Larrañaga (2008) Inference of Population Structure Using Genetic Markers and a Bayesian Model Averaging Approach for Clustering. Journal of Computational Biology, 15(2), 207-220.
R. Sagarna, J.A. Lozano (2008) Dynamic Search Space Transformations for Software Test Data Generation. Computational Intelligence, 24(1), 23-61.
R. Armañanzas, I. Inza, R. Santana, Y. Saeys, J. L. Flores, J. A. Lozano, Y. Van de Peer, R. Blanco, V. Robles, C. Bielza, P. Larrañaga (2008) A review of estimation of distribution algorithms in bioinformatics. BioData Mining, 1:6.
R. Santana, P. Larrañaga, J.A. Lozano (2008) Protein folding in simplified models with estimation of distribution algorithms. IEEE Transactions On Evolutionary Computation. Vol. 12. No. 4. Pp. 418-438.
R. Santana, P. Larrañaga, J.A. Lozano (2008) Combining variable neighborhood search and estimation of distribution algorithms in the protein side placement problem. Journal of Heuristics. Vol 14. Pp 519-547.
B. Calvo, J.A. Lozano, P. Larrañaga (2007) Learning Bayesian classifiers from positive and unlabeled examples. Pattern Recognition Letters, 28(16), 2375-2384.
B. Calvo, N. López-Bigas, S.J. Fureny, P. Larrañaga J.A. Lozano (2007) A partially supervised classification approach to dominant and recessive human disease gene prediction. Computer Methods and Programs in Biomedicine, 85(3), 229-237.
R. Santana, P. Larrañaga, and J.A. Lozano (2007) Side chain placement using estimation of distribution algorithms. Artificial Intelligence in Medicine, 39(1), 49-63.
G. Santafé, J.A. Lozano, P. Larrañaga (2006) Bayesian model averaging of naive Bayes for clustering. IEEE Transactions on Systems, Man, and Cybernetics - Part B, 36(5), 1149-1161.
P. Larrañaga, B. Calvo, R. Santana, C. Bielza, J. Galdiano, I. Inza, J.A. Lozano, R. Armañanzas, G. Santafé, A. Perez, V. Robles. (2006) Machine learning in bioinformatics. Briefings in Bioinformatics, 7(1), 86-112.
A. Mendiburu, J. Miguel-Alonso, J.A. Lozano, M. Ostra, C. Ubide (2006) Parallel EDAs to create multivariate calibration models for quantitative chemical applications. Journal of Parallel and Distributed Computing, 66(8), 1002-1013.
A. Mendiburu, J. Miguel-Alonso, J.A. Lozano (2006) Implementation and Performance evaluation of a parallelization of Estimation of Bayesian Network Algorithms. Parallel Processing Letters, 16(1), 133-148.
R. Sagarna, J.A. Lozano (2006) Scatter search in software testing, comparison and collaboration with Estimation of Distribution Algorithms. European Journal of Operational Research, 169(2), 392-412.
P. Larrañaga, J.A. Lozano, J.M. Peña, I. Inza (2005) Special Issue on Probabilistic Graphical Models for Classification. Machine Learning, 59(3).
P. Larrañaga, J.A. Lozano(2005) Special Issue on Estimation of Distribution Algorithms. Evolutionary Computation, 13(1), V-VI.
J.M. Peña, J.A. Lozano, P. Larrañaga (2005) Globally multimodal problem optimization via an Estimation of Distribution Algorithm based on unsupervised learning of Bayesian networks. Evolutionary Computation, 13(1), 43-66.
A. Mendiburu, J.A. Lozano, J. Miguel-Alonso (2005) Parallel implementation of EDAs based on probabilistic graphical models. IEEE Transactions On Evolutionary Computation, 9(4), 406-423.
R. Sagarna, J.A. Lozano (2005) On the performance of Estimation of Distribution Algorithms applied to software testing. Applied Artificial Intelligence, 19(5), 457-489.
J.M. Peña, J.A. Lozano, P. Larrañaga (2004) 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 (1), 63-82.
P. Larrañaga, J.A. Lozano (2002) Synergies between evolutionary computation and probabilistic graphical models. International Journal of Approximate Reasoning, 31, 155-156.
C. González, J.A. Lozano, P. Larrañaga (2002) Mathematical modelling of UMDAc algorithm with tournament selection. Behaviour on linear and quadratic functions. International Journal of Approximate Reasoning, 31(3), 313-340.
J.M. Peña, J.A. Lozano, P. Larrañaga (2002) Learning recursive Bayesian multinets for clustering by means of constructive induction. Machine Learning, 47(1), 63-90.
J.M. Peña, J.A. Lozano, P. Larrañaga (2001) Performance evaluation of compromise conditional Gaussian networks for data clustering. International Journal of Approximate Reasoning, 28(1), 23-50.
J.M. Peña, J.A. Lozano, P. Larrañaga, I. Inza (2002) Dimensionality reduction in unsupervised learning of conditional Gaussian networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(6), 590-603.
C. González, J.A. Lozano, P. Larrañaga (2000) Analyzing the PBIL algorithm by means of discrete dynamical systems. Complex Systems, 12(4), 465-479.
J.M. Peña, J.A. Lozano, P. Larrañaga. (2000) An improved Bayesian structural EM algorithm for learning Bayesian networks for clustering. Pattern Recognition Letters, 21(8), 779-786.
J.M. Peña, J.A. Lozano, P. Larrañaga (1999) Learning Bayesian networks for clustering by means of constructive induction. Pattern Recognition Letters, 20 (11-13), 1219-1230.
I. Inza, P. Larrañaga, B. Sierra, R. Etxeberria, J.A. Lozano, J.M. Peña (1999) Representing the joint behaviour of machine learning inducers by Bayesian networks. Pattern Recognition Letters, 20 (11-13), 1201-1209.
J.M. Peña, J.A. Lozano, P. Larrañaga (1999) An empirical comparison of four initialization methods for the k-means algorithm. Pattern Recognition Letters, 20 (10), 1027-1040.
J.A. Lozano, P. Larrañaga (1999) Applying genetic algorithms to search for the best hierarchical clustering of a dataset. Pattern Recognition Letters, 20 (9), 911-918.
J.A. Lozano, P. Larrañaga, M. Graña, F.X. Albizuri (1999) Genetic algorithms: bridging the convergence gap. Theoretical Computer Science, 229, 11-22.
F.X. Albizuri, A. D'Anjou, M. Graña, J.A. Lozano (1996) Convergence Properties of High-order Boltzmann Machines. Neural Networks, 9(9), 1561-1567.

Jose A. Lozano