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Publications of Author

1. Roberto Santana
   A Markov Network Based Factorized Distribution Algorithm for Optimization. [Citation Graph (0, 0)][DBLP]
   ECML, 2003, pp:337-348 [Conf]
   
2. Roberto Santana, Pedro Larrañaga, José Antonio Lozano
   Mixtures of Kikuchi Approximations. [Citation Graph (0, 0)][DBLP]
   ECML, 2006, pp:365-376 [Conf]
   
3. Roberto Santana, Alberto Ochoa-Rodríguez, Marta Sota, Francisco B. Pereira, Penousal Machado, Ernesto Costa, Amílcar Cardoso
   Probabilistic Evolution and the Busy Beaver Problem. [Citation Graph (0, 0)][DBLP]
   GECCO, 2000, pp:380- [Conf]
   
4. 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]
   
5. 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]
   
6. Roberto Santana
   Estimation of Distribution Algorithms with Kikuchi Approximations. [Citation Graph (0, 0)][DBLP]
   Evolutionary Computation, 2005, v:13, n:1, pp:67-97 [Journal]
   
7. 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]
   
8. Alexander Mendiburu, Roberto Santana, Jose Antonio Lozano, Endika Bengoetxea
   A parallel framework for loopy belief propagation. [Citation Graph (0, 0)][DBLP]
   GECCO (Companion), 2007, pp:2843-2850 [Conf]
   
9. 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]
   
10. 
    Using Probabilistic Dependencies Improves the Search of Conductance-Based Compartmental Neuron Models. [Citation Graph (, )][DBLP]
    
    
11. 
    An EDA based on local markov property and gibbs sampling. [Citation Graph (, )][DBLP]
    
    
12. 
    Mining probabilistic models learned by EDAs in the optimization of multi-objective problems. [Citation Graph (, )][DBLP]
    
    
13. 
    Adding Probabilistic Dependencies to the Search of Protein Side Chain Configurations Using EDAs. [Citation Graph (, )][DBLP]
    
    
14. 
    Exact Bayesian network learning in estimation of distribution algorithms. [Citation Graph (, )][DBLP]
    
    
15. 
    Component weighting functions for adaptive search with EDAs. [Citation Graph (, )][DBLP]
    
    
16. 
    Analyzing the probability of the optimum in EDAs based on Bayesian networks. [Citation Graph (, )][DBLP]
    
    
17. 
    Side chain placement using estimation of distribution algorithms. [Citation Graph (, )][DBLP]