Roberto Santana Monte Igeldo

Roberto Santana

Tenured researcher

Intelligent Systems Group
Department of Computer Science and Artificial Intelligence
University of the Basque Country
Paseo Manuel de Lardizábal 1, CP-20080
San Sebastián - Donostia, Spain  

telefon + 34 943 01 8556 email roberto.santana AT ehu.es


Research Interests
  • Estimation of Distribution Algorithms
  • Computational Neuroscience
  • Probabilistic Graphical Models
  • Bioinformatics


Recent Publications



2017
 

A. Strickler, O. Rodrigues-Castro, A. Pozo, and R. Santana. An investigation of the selection strategies impact on MOEDAs: CMA-ES and UMDA. Applied Soft Computing. Accepted for publication. 2017.

M. S. R. Martins, M. Delgado, R. Lueders, R. Santana, R. A. Goncalves, and C. P. de Almeida. Hybrid Multi-objective Bayesian Estimation of Distribution Algorithm: A comparative analysis for the multi-objective knapsack problem. Journal of Heuristics. Accepted for publication. 2017.

O. Rodrigues-Castro, A. Pozo, J. A. Lozano, and R. Santana. An investigation of clustering strategies in many-objective optimization: the I-Multi algorithm as a case study. Swarm Intelligence. Vol. 11. No. 2. Pp. 101-130. 2017.

M. Zangari, A. Pozo, R. Santana, and A. Mendiburu. A decomposition-based binary ACO algorithm for the multiobjective UBQP. Neurocomputing. Vol. 246. Pp. 58-68. 2017.

O. Rodrigues-Castro, A. Pozo, J. A. Lozano, and R. Santana. Transfer weight functions for injecting problem information in the Multi-Objective CMA-ES. Memetic Computing.Vol. 9, No. 2, Pp. 153-180. 2017.

M. Zangari, R. Santana, A. Mendiburu, and A. Pozo. Not all PBILs are the same: Unveiling the different learning mechanisms of PBIL variants. Applied Soft Computing. Vol. 53. Pp. 88-96. 2017.

R. Santana and J. A. Lozano. Different scenarios for survival analysis of evolutionary algorithms. In Proceedings of the 2017 Genetic and Evolutionary Conference (GECCO-2017), Berlin, Germany. Pp. 825-832. 2017.

R. Santana, G. Sirbiladze, B. Ghvaberidze and B. Matsaberidze. A comparison of probabilistic-based optimization approaches for vehicle routing problems. In Proceedings of the 2017 Congress on Evolutionary Computation (CEC-2017), San Sebastian, Spain. IEEE Press.   Pp. 2606-2613. 2017.

V. Fontoura, A. Pozo and R. Santana. Automated Design of Hyper-Heuristics Components to Solve the PSP Problem with HP Model. In Proceedings of the 2017 Congress on Evolutionary Computation (CEC-2017), San Sebastian, Spain. IEEE Press.   Pp. 1848-1855. 2017.

O. Rodrigues-Castro, J. A. Lozano, R. Santana and A. Pozo. Combining CMA-ES and MOEA/DD for many-objective optimization. In Proceedings of the 2017 Congress on Evolutionary Computation (CEC-2017), San Sebastian, Spain. IEEE Press.   Pp. 1451-1458. 2017.

M. S. R. Martins, M. Delgado, R. Lueders, R. Santana, R. A. Goncalves, and C. P. de Almeida. Probabilistic analysis of Pareto front approximation for a hybrid multi-objective Bayesian estimation of distribution algorithm. In Proceedings of the Brazilian Conference on Intelligent Systems (BRACIS 2017), Uberlandia, Brazil.   Accepted for publication. 2017.

R. H. R. Lima, V. Fontoura, A. Pozo and R. Santana. Multi-objective approach to the Protein Structure Prediction Problem. Chapter 8 in Evolutionary Multi-Objective System Design: Theory and Applications.   Computer and Information Science Series. Chapman & Hall/CRC.  In Press. 2017.

 




2016
 

D. Carrera, R. Santana, and J. A. Lozano. Vine copula classifiers for the mind reading problem. Progress in Artificial Intelligence. Vol 5 (4). Pp. 289-305. 2016.

O. Rodrigues-Castro, R. Santana, A. Pozo. C-Multi: a competent multi-swarm approach for many-objective problems. Neurocomputing. Vol. 180, Pp. 68-78. 2016.

R. Santana, A. Mendiburu, and J. A. Lozano. A review of message passing algorithms in estimation of distribution algorithms. Natural Computing. Vol. 15 (1), Pp. 165-180. 2016.

A. Astigarraga, A. Arruti, J. Muguerza, R. Santana, J. I. Martin, and B. Sierra. User Adapted Motor-Imaginary Brain-Computer Interface by means of EEG Channel Selection based on Estimation of Distributed Algorithms. Mathematical Problems in Engineering. Article ID 1435321, 12 pages. 2016.

S. Picek, R. Santana, D. Jakobovic. Maximal Nonlinearity in Balanced Boolean Functions with Even Number of Inputs, Revisited. In Proceedings of the 2016 Congress on Evolutionary Computation (CEC-2016), Vancouver, Canada. IEEE Press.   Pp. 3222-3229. 2016.

M. Zangari, R. Santana, A. Mendiburu, and A. Pozo. On the design of hard mUBQP instances. In Proceedings of the The 2016 Genetic and Evolutionary Conference (GECCO-2016), Denver, CO., USA.   Pp. 421-428. 2016.

R. Santana, Z. Zhu, and H. Katzgraber. Evolutionary approaches to optimization problems in Chimera topologies. In Proceedings of the The 2016 Genetic and Evolutionary Conference (GECCO-2016), Denver, CO., USA.  . Pp. 397-404. 2016.

M. S. R. Martins, M. Delgado, R. Santana, R. Lueders, R. A. Goncalves, and C. P. de Almeida. HMOBEDA: Hybrid Multi-objective Bayesian Estimation of Distribution Algorithm. In Proceedings of the The 2016 Genetic and Evolutionary Conference (GECCO-2016), Denver, CO., USA.   Pp 357-364. 2016.

U. Garciarena and R. Santana. Evolutionary optimization of compiler flag selection by learning and exploiting flags interactions. In Workshop on the Repair and Optimisation of Software using Computational Search (Genetic Improvement - 2016). Companion proceedings of the 2016 Genetic and Evolutionary Conference (GECCO-2016), Denver, CO., USA.   Pp. 1159-1166. 2016.

A. Strickler, O. Rodrigues-Castro, R. Santana, and A. Pozo. Investigating selection strategies in multi-objective probabilistic model based algorithms. In Proceedings of the 2016 5th Brazilian Conference on Intelligent Systems (BRACIS 2016). Recife, Pernambuco.   Pp. 7-12. IEEE press. 2016.

 




2015
 

C. Echegoyen, R. Santana, A. Mendiburu, and J. A. Lozano. Comprehensive Characterization of the Behaviors of Estimation of Distribution Algorithms. Theoretical Computer Science. Accepted for publication. 2015.

R. Santana, A. Mendiburu, and J. A. Lozano. Multi-view classification of psychiatric conditions based on saccades. Applied Soft Computing. Vol. 31. Pp. 308-316. 2015.

S. Picek, B. McKay, R. Santana, T. Gedeon. Fighting the Symmetries: The Structure of Cryptographic Boolean Function Spaces. In Proceedings of the The 2015 Genetic and Evolutionary Conference (GECCO-2015), Madrid, Spain.   Pp. 457-464. 2015.

R. Santana, A. Mendiburu, and J. A. Lozano. Multi-objective NM-landscapes. In Proceedings of the The 2015 Genetic and Evolutionary Conference (GECCO-2015), Madrid, Spain.   Pp. 1477-1478. 2015.

W.-L Zheng, R. Santana, B.-L Lu. Comparison of Classification Methods for EEG-based Emotion Recognition. In World Congress on Medical Physics and Biomedical Engineering , Toronto, Canada. Pp. 1184-1187. 2015.

J. Ceberio, R. Santana, A. Mendiburu, and J. A. Lozano. Mixtures of Generalized Mallows models for solving the Quadratic Assignment Problem. In Proceedings of the 2015 Congress on Evolutionary Computation (CEC-2015), Sendai, Japan. IEEE Press.   Pp. 2050-2057. 2015.

R. Santana, A. Mendiburu, and J. A. Lozano. Evolving MNK-landscapes with structural constraints. In Proceedings of the 2015 Congress on Evolutionary Computation (CEC-2015), Sendai, Japan. IEEE Press.   Pp. 1364-1371. 2015.

R. Santana. Supervised classification of vowel speech imagery. In Memorias Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA-2015), Albacete, Spain.   Accepted for publication. 2015.

G. Fritsche, A. Strickler, A. Pozo, and R. Santana. Capturing Relationships in Multi-Objective Optimization. In Proceedings of the Brazilian Conference on Intelligent Systems (BRACIS 2015), Natal, Brazil.   Accepted for publication. 2015.

J. Santamaría, J. Ceberio, R. Santana, A. Mendiburu, and J. A. Lozano. Introducing Mixtures of Generalized Mallows in Estimation of Distribution Algorithms. In Proceedings of the X Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB-2015), Merida, Spain.   Pp. 97-102. 2015.

I. Roman, R. Santana, A. Mendiburu, and J. A. Lozano. Kernel hautapen dinamikoa Optimizazio Bayesiarrean. Ikertzaile Euskaldunen Lehen Kongresua, Durango, Spain. Accepted for presentation. 2015.

R. Santana, A. Mendiburu, and J. A. Lozano. Computing factorized approximations of Pareto-fronts using mNM-landscapes and Boltzmann distributions. In Memorias Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA-2015), Albacete, Spain.   Accepted for publication. 2015.

M. Zangari, R. Santana, A. Mendiburu, and A. Pozo. PBIL: un mismo nombre para distintos algoritmos. Un caso de estudio sobre un problema de optimización multi-objetivo. In Memorias de las II Jornadas sobre Algoritmos Evolutivos y Metaheuristicas (JAEM 2015), Albacete, Spain.   Accepted for publication. 2015.

V. D. Da Fontoura, R. Remes de Lima, A. Pozo, and R. Santana. Algoritmos multiobjetivos aplicados ao problema de predicao de estruturas proteínas. In Memorias del 12 Congresso Brasileiro de Inteligencia Computacional (CBIC 2015), Curitiba, Brazil.   Accepted for publication. 2015.

 




2014
 

H. Karshenas, R. Santana, C. Bielza,  and P. Larrañaga. Multi-objective estimation of distribution algorithm based on joint modeling of objectives and variables. IEEE Transactions on Evolutionary Computation. Vol. 18. No. 4. Pp. 519-542. 2014. IEEE press.

R. Santana, A. Mendiburu, and J. A. Lozano. Customized selection in estimation of distribution algorithms. In Proceedings of the Tenth International Conference on Simulated Evolution And Learning (SEAL-2014). Dunedin, New Zealand. Lecture Notes in Computer Science Volume 8886, pp 94-105. 2014

R. Santana, R. B. McDonald, and H. G. Katzgraber. A probabilistic evolutionary optimization approach to compute quasiparticle braids." In Proceedings of the Tenth International Conference on Simulated Evolution And Learning (SEAL-2014). Dunedin, New Zealand. Lecture Notes in Computer Science Volume 8886, pp 13-24. 2014.

Ibai Roman, R. Santana, A. Mendiburu, and J. A. Lozano. Dynamic Kernel Selection Criteria for Bayesian Optimization. In Accepted for presentation at NIPS 2014 workshop on Bayesian optimization (NIPS-BayesOpt-2014). Nevada, USA.

 




2013
 

R. Santana, L. McGarry, C. Bielza, P. Larrañaga, and R. Yuste. Classification of neocortical interneurons using affinity propagation. Frontiers in Neural Circuits. 2013. Accepted for publication.

R. Santana, R. Armañanzas, C. Bielza,  and P. Larrañaga. Network measures for information extraction in evolutionary algorithms. International Journal of Computational Intelligence Systems. Vol. 6. No. 6. Pp. 1163-1188. 2013.

C. Echegoyen, A. Mendiburu, R. Santana, and J. A. Lozano. On the Taxonomy of Optimization Problems under Estimation of Distribution Algorithms. Evolutionary Computation. Vol. 3. Number 3. Pp. 471-495. 2013.

H. Karshenas, R. Santana, C. Bielza,  and P. Larrañaga. Regularized Continuous Estimation of Distribution Algorithms. Applied Soft Computing. Vol. 13. No. 5. Pp. 2412-2432. 2013.

P. Larrañaga, H. Karshenas, C. Bielza,  and  R. Santana. A Review on Evolutionary Algorithms in Bayesian Network Learning and Inference Tasks. Information Sciences. Vol. 233. No. 1. Pp. 109-125. 2013.

R. Santana, A. Mendiburu, and J. A. Lozano. Analyzing probabilistic models generated by EDAs for simplified protein folding problems. In Proceedings of the NIPS Workshop on Constructive Machine Learning (NIPS-CML-2013). Nevada, USA. Accepted for publication.

R. Santana, A. Mendiburu, and J. A. Lozano. Extending the use of message passing algorithms to problems with unknown structure. In Accepted for presentation at NIPS 2013 workshop on Bayesian optimization (NIPS-BayesOpt-2013). Nevada, USA.

R. Santana. Multi-objective optimization approach to detecting extremal patterns in social networks. In Proceedings of the Third World Congress on Information and Communication Technologies (WICT-2013), Hanoi, Vietnam. Accepted for publication. IEEE-Press 2013.

R. Santana, A. Mendiburu, and J. A. Lozano. Model-based template-recombination in Markov network estimation of distribution algorithms for problems with discrete representation. In Proceedings of the Third World Congress on Information and Communication Technologies (WICT-2013), Hanoi, Vietnam. Accepted for publication. IEEE-Press 2013.

R. Santana, C. Bielza,  and P. Larrañaga. Changing conduction delays to maximize the number of polychronous groups with an estimation of distribution algorithm. Technical Report UPM-FI/DIA/2013-1, Department of  Artificial Intelligence, Faculty of Informatics, Technical University of  Madrid. September, 2013. 

R. Santana, A. Mendiburu, and J. A. Lozano. Critical issues in model-based surrogate functions in estimation of distribution algorithms.. In Proceedings of the International Conference on Swarm Evolutionary and Memetic Computing (SEMCCO-2013), Chennai, India. Lecture Notes in Computer Science. Volume 8298. pp 1-13. 2013.

R. Santana, A. Mendiburu, and J. A. Lozano. Message passing methods for estimation of distribution algorithms based on Markov networks.. In Proceedings of the International Conference on Swarm Evolutionary and Memetic Computing (SEMCCO-2013), Chennai, India. Lecture Notes in Computer Science. Volume 8298. pp 419-430. 2013.

R. Santana, R. I. McKay, and J. A. Lozano. Symmetry in evolutionary and estimation of distribution algorithms. In Proceedings of the 2013 Congress on Evolutionary Computation (CEC-2013), Cancun, Mexico. IEEE Press.   Pp. 2053-2060. 2013.

 




2012
 

S. Shakya and  R. Santana. (Eds.). Markov Networks in Evolutionary Algorithms. Adaptation, Learning and Optimization series. Vol. 14. Springer.  2012.

R. Santana, C. Bielza,  and P. Larrañaga. Regularized logistic regression and multi-objective variable selection for classifying MEG data. Biological Cybernetics. Vol. 106. No. 6-7. Pp. 389-405. 2012.

C. Echegoyen, A. Mendiburu, R. Santana, and J. A. Lozano. Towards understanding EDAs based on Bayesian networks through a quantitative analysis. IEEE Transactions on Evolutionary Computation. 2012. Vol. 16. No. 2. Pp. 173-189.

P. Larrañaga, H. Karshenas, C. Bielza,  and  R. Santana. A review on probabilistic graphical models in evolutionary computation. Journal of Heuristics. Vol. 18. No. 5. Pp. 785-819. 2012.

S. Shakya, R. Santana,  and  J. A. Lozano.  A Markovianity based Optimisation Algorithm. Genetic Programming and Evolvable Machines. Springer.  Vol. 13. No. 2. Pp. 159-195. 2012

R. Santana,  L. Bonnet,  J. Legeny, and   A. Lecuyer. Introducing the use of model-based evolutionary algorithms for EEG-based motor imagery classification. In Proceedings of the 2012 Genetic and Evolutionary Conference (GECCO-2012), Philadelphia, US. ACM Digital Library. Pp. 1159-1166.  2012. 

R. Santana, A. Mendiburu, and J. A. Lozano. Evolving NK-complexity for evolutionary solvers. In Companion Proceedings of the 2012 Genetic and Evolutionary Conference (GECCO-2012), Philadelphia, US. ACM Digital Library. Pp. 1473-1474.  2012. 

R. Santana,  C. Bielza,  and  P. Larrañaga. Maximizing the number of polychronous groups in spiking networks. In Companion Proceedings of the 2012 Genetic and Evolutionary Conference (GECCO-2012), Philadelphia, US. ACM Digital Library. Pp. 1499-1500.  2012. 

R. Santana, A. Mendiburu and J. A. Lozano. Structural transfer using EDAs: An application to multi-marker tagging SNP selection. In Proceedings of the 2012 Congress on Evolutionary Computation (CEC-2012), Brisbane, Australia. IEEE Press.   Pp. 3484-3491. 2012. (Best CEC Paper)

R. Santana, A. Mendiburu and J. A. Lozano. An analysis of the use of probabilistic modeling for synaptic connectivity prediction from genomic data. In Proceedings of the 2012 Congress on Evolutionary Computation (CEC-2012), Brisbane, Australia. IEEE Press.   Pp. 3221--3228. 2012.

R. Santana and S. Shakya. Probabilistic Graphical Models and Markov Networks. Chapter 1 in Markov Networks in Evolutionary Algorithms.   Adaptation, Learning and Optimization. series Vol. 14. Springer.  2012. Pp. 3-19. 2012.

S. Shakya and R. Santana. A Review of Estimation of Distribution Algorithms and Markov Networks Probabilistic Graphical Models and Markov Networks. Chapter 2 in Markov Networks in Evolutionary Algorithms.   Adaptation, Learning and Optimization. series Vol. 14. Springer.  2012. Pp. 21-37. 2012.

S. Shakya and R. Santana. MOA - Markovian Optimisation Algorithm. Chapter 3 in Markov Networks in Evolutionary Algorithms.   Adaptation, Learning and Optimization. series Vol. 14. Springer.  2012. Pp. 39-53. 2012.

R. Santana.MN-EDA and the Use of Clique-Based Factorisations in EDAs. Chapter 5 in Markov Networks in Evolutionary Algorithms.   Adaptation, Learning and Optimization. series Vol. 14. Springer.  2012. Pp. 73-87. 2012.

R. Santana, A. Mendiburu and J. A. Lozano. Fast Fitness Improvements in Estimation of Distribution Algorithms Using Belief Propagation. Chapter 9 in Markov Networks in Evolutionary Algorithms.   Adaptation, Learning and Optimization. series Vol. 14. Springer.  2012. Pp. 141-155. 2012.

H. Karshenas, R. Santana, C. Bielza,  and  P. Larrañaga. Continuous Estimation of Distribution Algorithms Based on Factorized Gaussian Markov Networks. Chapter 10 in Markov Networks in Evolutionary Algorithms.   Adaptation, Learning and Optimization. series Vol. 14. Springer.  2012. Pp. 157-173. 2012.

R. Santana, C. Bielza,  and  P. Larrañaga. Multi-objective optimization approach to the analysis of inter-subject and inter-session variability in BCI experiments. Accepted for poster presentation at the International Joint Conference on Neural Networks (IJCN-2012), Brisbane, Australia.   2012.

H. Karshenas R. Santana, C. Bielza,  and P. Larrañaga. Multi-objective Estimation of Distribution Algorithm Based on Joint Modeling of Objectives and Variables. Technical Report UPM-FI/DIA/2012-2, Department of  Artificial Intelligence, Faculty of Informatics, Technical University of  Madrid. September, 2012. 

R. Santana, A. Mendiburu, and J. A. Lozano.  New methods for generating populations in Markov network based EDAs: Decimation strategies and model-based template recombination.  Technical Report EHU-KZAA-TR-5/2012, Department of Computer Science and Artificial Intelligence, University of the Basque Country, December 2012.

R. Santana, A. Mendiburu, and J. A. Lozano.  Using network measures to test evolved NK-landscapes.  Technical Report EHU-KZAA-TR-3/2012, Department of Computer Science and Artificial Intelligence, University of the Basque Country, July 2012.


 




2011

 

R. Santana,  C. Bielza,  and  P. Larrañaga.   Optimizing brain networks topologies using multi-objective evolutionary computation. Neuroinformatics. Vol. 9. No. 1. Pp. 3-19. 2011.

L. Lozada-Chang  and  R. Santana Univariate marginal distribution algorithm dynamics for a class of parametric functions with unitation constraints. Information Sciences.  Vol. 181. Pp. 2340-2355. 2011.

R.Santana. Estimation of distribution algorithms: from available implementations to potential developments. In Companion Proceedings of the 2011 Genetic and Evolutionary Conference (GECCO-2011), Dublin, Ireland. ACM Digital Library. Pp. 679-686.  2011. 

R. Santana,  S. Muelas, A. LaTorre, J. M. Peña. A Direct Optimization Approach to the P300 Speller. In Proceedings of the 2011 Genetic and Evolutionary Conference (GECCO-2011), Dublin, Ireland. ACM Digital Library.  Pp. 1747-1754. 2011.    

R. Santana,  H. Karshenas, C. Bielza, and P. Larrañaga. Regularized k-order Markov Models in EDAs. In Companion Proceedings of the 2011 Genetic and Evolutionary Conference (GECCO-2011), Dublin, Ireland. ACM Digital Library. Pp. 593-600.  2011.   

R. Santana,  C. Bielza, and P. Larrañaga. Affinity Propagation Enhanced by Estimation of Distribution Algorithms. In Proceedings of the 2011 Genetic and Evolutionary Conference (GECCO-2011), Dublin, Ireland. ACM Digital Library.  Pp. 331-338. 2011.  

R. Santana,  H. Karshenas, C. Bielza, and P. Larrañaga. Quantitative Genetics in Multi-Objective Optimization Algorithms: From Useful Insights to Effective Methods. In  Proceedings of the 2011 Genetic and Evolutionary Conference (GECCO-2011), Dublin, Ireland. ACM Digital Library.  Pp. 91-92.  2011.    

A. LaTorre, S. Muelas, J. M. Pena, R. Santana, A. Merchan-Perez and J. R. Rodriguez Differential evolution algorithm for the detection of synaptic vesicles. In Proceedings of the 2011 Congress on Evolutionary Computation (CEC-2011), New Orleans, U.S. IEEE Press. Pp. 1687-1694. 2011.

C. Echegoyen, Q. Zhang, A. Mendiburu, R. Santana, and J. A. Lozano. On the limits of effectiveness in estimation of distribution algorithms. In Proceedings of the of the 2011 Congress on Evolutionary Computation (CEC-2011), New Orleans, U.S. IEEE Press.Pp. 1573-1580.   2011.

H. Karshenas, R. Santana, C. Bielza and P. Larrañaga. Multi-objective optimization with joint  probabilistic modeling of objectives and variables. In Proceedings of the Evolutionary Multi-objective Optimization Conference (EMO-2011). Lecture Notes in Computer Science. Springer-Verlag, Brazil.  Pp. 298-312. 2011.
 
C. Echegoyen, Q. Zhang, A. Mendiburu, R. Santana, and J. A. Lozano.  Analyzing limits of effectiveness in different implementations of estimation of distribution algorithms.  Technical Report EHU-KZAA-TR-2/2011, Department of Computer Science and Artificial Intelligence, University of the Basque Country, January 2011.
 
H. Karshenas, R. Santana, C. Bielza and P. Larrañaga. Regularized model learning in estimation of distribution algorithms for continuous optimization problems. Technical Report UPM-FI/DIA/2011-1, Department of  Artificial Intelligence, Faculty of Informatics, Technical University of  Madrid. January, 2011. 
 




2010

R. Santana, A. Mendiburu, N. Zaitlen, E. Eskin and J. A. Lozano. Multi-marker tagging SNP selection using estimation of distribution algorithms. Artificial Intelligence in Medicine.  Vol. 5 No. 3. Pp. 193-201. 2010.
 

H. Karshenas, R. Santana, C. Bielza, and P. Larrañaga. Multi-Objective Decomposition with Gaussian Bayesian Networks. In International Conference on Metaheuristics and Nature Inspired Computing META-2010, Djerba, Tunisia.  Accepted for presentation. 2010.

R. Santana, C. Bielza and P. Larrañaga. Network measures for re-using problem information in EDAs. Technical Report UPM-FI/DIA/2010-3, Department of  Artificial Intelligence, Faculty of Informatics, Technical University of  Madrid. June, 2010.

C. Echegoyen, A. Mendiburu, R. Santana, and J.A. Lozano. Estimation of Bayesian networks algorithms in a class of complex networks. In Proceedings of the 2010 Congress on EvolutionaryComputation (CEC-2010), Barcelone, Spain. IEEE Press.  2010.

A. Cuesta-Infante, R. Santana, C. Bielza, and P. Larrañaga, and J. I. Hidalgo. Bivariate empirical and n-variate Archimedean copulas in estimation of distribution algorithms. In Proceedings of the 2010 Congress on Evolutionary Computation (CEC-2010), Barcelone, Spain. IEEE Press.
 
R. Santana, C. Bielza, and P. Larrañaga. Classification of MEG data using a combined machine learning approach. Accepted for presentation at the  Workshop Data analysis competition: Connectivity and multivariate classification approaches of the 17th International Conference of Biogmagnetism. Dubrovnik, Croacia.  2010.
 
R. Santana, C. Bielza, and P. Larrañaga. Synergies between network-based representation and probabilistic graphical models for classification, inference and optimization problems in neurosciences. In Proceedings of the Twenty Third International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA-AIE 2010). Lecture Notes in Computer Science. Springer-Verlag, Cordoba-Spain. Accepted for publication. 2010.

R. Santana, C. Bielza, and P. Larrañaga. Using probabilistic dependencies improves the search of conductance-based compartmental neuron models. In Proceedings of the Seventh European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics (EVO-BIO). Lecture Notes in Computer Science. Springer-Verlag Istambul-Turkey. Accepted for publication. 2010.

R. Santana, C. Bielza, P. Larrañaga, J. A. Lozano,  C. Echegoyen, A. Mendiburu,   R. Armañanzas, and S. Shakya. Mateda2.0: Estimation of distribution algorithms in MATLAB Journal of Statistical Software.  Vol. 35 No. 7 Pp. 1-30. 2010.
 
C. Echegoyen, A. Mendiburu, R. Santana, and J. A. Lozano. Analyzing the k Most Probable Solutions in EDAs based on Bayesian NetworksIn Exploitation of linkage learning in evolutionary algorithms. Evolutionary Learning and Optimization. Springer. Y.-P. Chen editor.
 
R. Santana, P. Larrañaga, and J. A. Lozano. Learning factorizations in estimation of distribution algorithms using affinity propagation.   Evolutionary Computation. Vol. 18. No. 4. Pp. 515-546. 2010




2009


C. Echegoyen, A. Mendiburu, R. Santana, J.A. Lozano. A quantitative analysis of estimation of distribution algorithms based on Bayesian networks. Technical Report EHU-KZAA-TR-2-2009, Department of Computer Science and Artificial Intelligence, University of the Basque Country, September 2009.

R. Santana, A. Mendiburu, N. Zaitlen, E. Eskin, and J. A. Lozano. On the application of estimation of distribution algorithms to multi-marker tagging SNP selection. Technical Report EHU-KZAA-IK-4/09, Department of Computer Science and Artificial Intelligence, University of the Basque Country, July 2009.

R. Santana, P. Larrañaga, and J. A. Lozano. Learning factorizations in estimation of distribution algorithms using affinity propagation.   Evolutionary Computation. Accepted for publication. 

R. Santana,  C. Bielza, J. A. Lozano, and P. Larrañaga. Mining probabilistic models learned by EDAs in the optimization of multi-objective problems.  In Proceedings of the 2009 Genetic and Evolutionary Conference (GECCO-2009) , Montreal, Canada. ACM Digital Library.  2009. Pp. 445-452.  

R. Santana, C. Echegoyen, A. Mendiburu, C. Bielza, J. A. Lozano, P. Larrañaga, R. Armañanzas and S. Shakya. MATEDA: A suite of EDA programs in Matlab. Technical Report EHU-KZAA-IK-2/09, Department of Computer Science and Artificial Intelligence, University of the Basque Country, February 2009. MATEDA code is available here.

C. Echegoyen, A. Mendiburu, R. Santana, and J. A. Lozano. Analyzing the probability of the optimum in EDAs based on Bayesian networks. In Proceedings of the 2009 Congress on Evolutionary Computation (CEC-2009), Norway, 2009. IEEE Press. Pp. 1652-1659.

C. Echegoyen, A. Mendiburu, R. Santana, and J. A. Lozano. Estudio de la probabilidad del optimo en EDAs basados en redes Bayesianas. In Proceedings of the VI Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB-2009), Malaga, Spain, 2009.

R. Santana, P. Larrañaga, and J. A. Lozano. Research topics in discrete estimation of distribution algorithms.   Memetic Computing. Vol 1. No. 1. Pp. 35-54. 



2008



S. Shakya and R. Santana. A Markovianity based Optimisation Algorithm. Technical Report EHU-KZAA-IK-3/08, Department of Computer Science and Artificial Intelligence, University of the Basque Country, September 2008.

R. Armañanzas, I. Inza, R. Santana, Y. Saeys, J. L. Flores, J. A. Lozano, Y. Van de Peer, R. Blanco, V. Robles, C. Bielza and P. Larrañaga. A review of estimation of distribution algorithms in bioinformatics.   BioData Mining. 1:6.  

R. Santana, P. Larrañaga, and Jose A. Lozano. Adding probabilistic dependencies to the search of protein side chain configurations using EDAs. In Proceedings of the 10th International Conference on Parallel Problem Solving From Nature (PPSM-2008). . Dortmund, Germany.   2008. Pp. 1120-1129.  

R. Santana, A. Mendiburu and Jose A. Lozano. An empirical analysis of loopy belief propagation in three topologies: grids, small-world networks and random graphs. In Proceedings of the Fourth European Workshop on Probabilistic Graphical Models (PGM-2008). Hirtshals, Denmark.   2008. Pp. 249-256.  

S. Shakya and R. Santana. An EDA based on local Markov property and Gibbs sampling. In Proceedings of the 2008 Genetic and Evolutionary Conference (GECCO-2008), Atlanta, US. ACM Digital Library.  2008. Pp. 475-476.  

C. Echegoyen, R. Santana, J. A. Lozano, and P. Larrañaga. The impact of probabilistic learning algorithms in EDAs based on Bayesian networks.   In Linkage in Evolutionary Algorithms. Studies in Computational Intelligence Series. Springer. Y.-P. Chen and M.-H. Lim editors. Pp. 109-139.   2008.

R. Santana, P. Larrañaga and J. A. Lozano. Component weighting functions for adaptive search with EDAs. In Proceedings of the 2008 Congress on Evolutionary Computation (CEC-2008), Hong Kong, 2008. IEEE Press. Pp 4067-4074.

R. Santana, P. Larrañaga, and J. A. Lozano. Protein folding in simplified models with  estimation of distribution algorithms.   IEEE Transactions on Evolutionary Computation. Vol. 12. No. 4. Pp. 418-438. 

R. Santana, J. A. Lozano, and P. Larrañaga. Adaptive estimation of distribution algorithms.   In Adaptive Metaheuristics. Studies in Computational Intelligence Series. Springer. C. Cotta, M. Sevaux and K. Soerensen editors. Pp. 177-197. 

R. Santana, P. Larrañaga, and J. A. Lozano. Learning factorizations in estimation of distribution algorithms using affinity propagation. Technical Report EHU-KZAA-IK-1/08, Department of Computer Science and Artificial Intelligence, University of the Basque Country, January 2008.

R. Santana, J. A. Lozano and P. Larrañaga. Combining variable neighborhood search and estimation of distribution algorithms in the protein side chain placement problem. Journal of Heuristics. Vol. 14. Pp 519-547.  



2007


R. Hoens, R. Santana, P. Larrañaga, and J. A. Lozano. Optimization by Max-Propagation Using Kikuchi Approximations. Technical Report EHU-KZAA-IK-2/07, Department of Computer Science and Artificial Intelligence, University of the Basque Country, November 2007.

A. Mendiburu, R. Santana, and J. A. Lozano. Introducing Belief Propagation in Estimation of Distribution Algorithms: A Parallel Approach. Technical Report EHU-KAT-IK-11-07, Department of Computer Science and Artificial Intelligence, University of the Basque Country, October 2007.

R. Santana, P. Larrañaga, and J. A. Lozano. Challenges and open problems in discrete EDAs. Technical Report EHU-KZAA-IK-1/07, Department of Computer Science and Artificial Intelligence, University of the Basque Country, October 2007.

C. Echegoyen, R. Santana, J. A. Lozano, and P. Larrañaga. Aprendizaje exacto de redes Bayesianas en algoritmos de estimación de distribuciones. In Memorias de las Jornadas de Algoritmos Evolutivos y Metaheurísticas (JAEM I).  Zaragoza, 2007. Pp. 277-284.

C. Echegoyen, J. A. Lozano, R. Santana,  and P. Larrañaga. Exact Bayesian network learning in estimation of distribution algorithms. In Proceedings of the 2007 Congress on Evolutionary Computation (CEC-2007), Singapore, 2007. IEEE Press. Pp. 1051-1058.

A. Mendiburu,  R. Santana,  J. A. Lozano, and E. Bengoetxea. A parallel framework for  loopy belief propagation.  In Workshops Proceedings of the 2007 Genetic and Evolutionary Conference (GECCO-2007), London, UK. ACM Digital Library.  2007. Pp. 2843-2850.  


R. Santana, J. A. Lozano and P. Larrañaga. The role of a priori information in the minimization of  contact potentials by means of estimation of distribution algorithms.   Proceedings of the Fifth European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics. Lecture Notes in Computer Science. Valencia,  2007. Pp. 247-257.

R. Santana, J. A. Lozano and P. Larrañaga.  Algoritmos de Estimación de Distribuciones para el problema de la determinación de la cadena lateral de una proteína.  Memorias del V Congreso Español de Algoritmos Evolutivos y Bioinspirados.  Tenerife, 2007. Pp. 663-670.

R. Santana, P. Larrañaga, and J. A. Lozano. Side chain placement using estimation of distribution algorithms. Artificial Intelligence in Medicine. 39(1). 2007. Pp. 49-63.


2006


P. Larrañaga, B. Calvo, R. Santana, C. Bielza, J. Galdiano, I. Inza, J. A. Lozano, R. Armañanzas, G. Santafé, A. Pérez and V. Robles. Machine learning in Bioinformatics. Briefings in Bioinformatics. 7. 2006. Pp. 86-112. [bib]

R. Santana, P. Larrañaga, and J. A. Lozano. Mixtures of Kikuchi approximations. Proceedings of the 17th European Conference on Machine Learning ( ECML-2006). Lecture Notes in Artificial Intelligence. Berlin, Germany. 2006. Pp. 365-376

2005
R. Santana. Estimation of distribution algorithms with Kikuchi approximations. Evolutionary Computation, 13(1):67-97, 2005.[ link ]

Y. M. Alvarez-Ginarte, R. Crespo, L. A. Montero-Cabrera, J. A. Ruiz-García, Y. M. Ponce, R. Santana, E. Pardillo-Fontdevila, and E. Alonso-Becerra. A novel in-silico approach for QSAR studies of anabolic and androgenic activities in the 17-hydroxy-5-androstane steroid family. QSAR & Combinatorial Science, 4:218-226, 2005.[ link ]

R. Santana, P. Larrañaga, and J. A. Lozano. Interactions and dependencies in Estimation of Distribution Agorithms. In Proceedings of the 2005 Congress on Evolutionary Computation (CEC-2005), Edinburgh, U.K., 2005. IEEE Press. Pp. 1418-1425.[ bib ]

R. Santana, P. Larrañaga, and J. A. Lozano. Aprendizaje y muestreo de la aproximación Kikuchi. In Proceedings of the III Taller Nacional de Minería de Datos y Aprendizaje (TAMIDA-2005), Granada, Spain, 2005. Thomson. Pp. 97-105.[ bib ]

R. Santana, P. Larrañaga, and J. A. Lozano. Protein structure prediction in simplified models with estimation of distribution algorithms. In Proceedings of the IV Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB-2005), Granada, Spain, 2005. Thomson. Pp. 245-252.[ bib ]

R. Santana, P. Larrañaga, and J. A. Lozano. Properties of Kikuchi approximations constructed from clique based decompositions. Technical Report EHU-KZAA-IK-2/05, Department of Computer Science and Artificial Intelligence, University of the Basque Country, April 2005.
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