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Inés María Galván: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Juan Manuel Alonso-Weber, Inés María Galván, Araceli Sanchis de Miguel
    Modified Self-organizing Maps for Line Extraction in Digitized Text Documents. [Citation Graph (0, 0)][DBLP]
    Applied Informatics, 2003, pp:281-286 [Conf]
  2. José María Valls, Inés María Galván, Pedro Isasi
    How the Selection of Training Patterns can Improve the Generalization Capability in Radial Basis Neural Networks. [Citation Graph (0, 0)][DBLP]
    Applied Informatics, 2003, pp:275-280 [Conf]
  3. César Estébanez, José María Valls, Ricardo Aler, Inés María Galván
    A First Attempt at Constructing Genetic Programming Expressions for EEG Classification. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2005, pp:665-670 [Conf]
  4. Germán Gutiérrez, Inés María Galván, José M. Molina, Araceli Sanchís
    Generative Capacities of Cellular Automata Codification for Evolution of NN Codification. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:314-322 [Conf]
  5. José María Valls, Inés María Galván, Pedro Isasi
    Lazy Training of Radial Basis Neural Networks. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2006, pp:198-207 [Conf]
  6. José María Valls, Pedro Isasi, Inés María Galván
    Deferring the Learning for Better Generalization in Radial Basis Neural Networks. [Citation Graph (0, 0)][DBLP]
    ICANN, 2001, pp:189-195 [Conf]
  7. Esteban García-Cuesta, Inés María Galván, Antonio J. de Castro
    Spectral High Resolution Feature Selection for Retrieval of Combustion Temperature Profiles. [Citation Graph (0, 0)][DBLP]
    IDEAL, 2006, pp:754-762 [Conf]
  8. German Gutiérrez Sanchez, Pedro Isasi, José M. Molina, Araceli Sanchís, Inés María Galván
    Evolutionary Cellular Configurations for Designing Feed-Forward Neural Networks Architectures. [Citation Graph (0, 0)][DBLP]
    IWANN (1), 2001, pp:514-521 [Conf]
  9. Pedro Isasi, José María Valls, Inés María Galván
    A Better Selection of Patterns in Lazy Learning Radial Basis Neural Networks. [Citation Graph (0, 0)][DBLP]
    IWANN (1), 2003, pp:278-285 [Conf]
  10. Esteban García-Cuesta, Inés María Galván, Antonio J. de Castro
    Neural Networks and Spectral Feature Selection for Retrieval of Hot Gases Temperature Profiles. [Citation Graph (0, 0)][DBLP]
    CIMCA/IAWTIC, 2005, pp:81-86 [Conf]
  11. José María Valls, José M. Molina, Inés María Galván
    Sistema Multiagente para el diseño de Redes de Neuronas de Base Radial Óptimas. [Citation Graph (0, 0)][DBLP]
    Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial, 2000, v:10, n:, pp:18-25 [Journal]
  12. José M. Molina, Inés María Galván, José María Valls, Andrés Leal
    Optimizing the Number of Learning Cycles in the Design of Radial Basis Neural Networks Using a Multi-Agent System. [Citation Graph (0, 0)][DBLP]
    Computers and Artificial Intelligence, 2001, v:20, n:5, pp:- [Journal]
  13. Germán Gutiérrez, Araceli Sanchís, Pedro Isasi Viñuela, José M. Molina, Inés María Galván
    Non-Direct Encoding Method Based on Cellular Automata to Design Neural Network Architectures. [Citation Graph (0, 0)][DBLP]
    Computers and Artificial Intelligence, 2005, v:24, n:3, pp:- [Journal]
  14. José María Valls, Inés María Galván, Pedro Isasi Viñuela
    Improving the Generalization Ability of RBNN Using a Selective Strategy Based on the Gaussian Kernel Function. [Citation Graph (0, 0)][DBLP]
    Computers and Artificial Intelligence, 2006, v:25, n:1, pp:- [Journal]
  15. Inés María Galván, Pedro Isasi, Ricardo Aler, José María Valls
    A Selective Learning Method to Improve the Generalization of Multilayer Feedforward Neural Networks. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2001, v:11, n:2, pp:167-177 [Journal]
  16. Inés María Galván, Pedro Isasi
    Multi-step Learning Rule for Recurrent Neural Models: An Application to Time Series Forecasting. [Citation Graph (0, 0)][DBLP]
    Neural Processing Letters, 2001, v:13, n:2, pp:115-133 [Journal]
  17. José María Valls, Inés María Galván, Pedro Isasi
    Lazy Learning in Radial Basis Neural Networks: A Way of Achieving More Accurate Models. [Citation Graph (0, 0)][DBLP]
    Neural Processing Letters, 2004, v:20, n:2, pp:105-124 [Journal]
  18. Alejandro Cervantes, Inés María Galván, Pedro Isasi
    An Adaptive Michigan Approach PSO for Nearest Prototype Classification. [Citation Graph (0, 0)][DBLP]
    IWINAC (2), 2007, pp:287-296 [Conf]
  19. Alejandro Cervantes, Inés María Galván, Pedro Isasi
    A comparison between the Pittsburgh and Michigan approaches for the binary PSO algorithm. [Citation Graph (0, 0)][DBLP]
    Congress on Evolutionary Computation, 2005, pp:290-297 [Conf]
  20. José María Valls, Inés María Galván, Pedro Isasi
    LRBNN: A Lazy Radial Basis Neural Network model. [Citation Graph (0, 0)][DBLP]
    AI Commun., 2007, v:20, n:2, pp:71-86 [Journal]

  21. Optimizing the DFCN Broadcast Protocol with a Parallel Cooperative Strategy of Multi-Objective Evolutionary Algorithms. [Citation Graph (, )][DBLP]


  22. Using Evolutionary Multiobjective Techniques for Imbalanced Classification Data. [Citation Graph (, )][DBLP]


  23. Discriminant Regression Analysis to Find Homogeneous Structures. [Citation Graph (, )][DBLP]


  24. A Lazy Approach for Machine Learning Algorithms. [Citation Graph (, )][DBLP]


  25. Multiobjective Algorithms Hybridization to Optimize Broadcasting Parameters in Mobile Ad-Hoc Networks. [Citation Graph (, )][DBLP]


  26. Supervised clustering via principal component analysis in a retrieval application. [Citation Graph (, )][DBLP]


  27. Improving Classification for Brain Computer Interfaces using Transitions and a Moving Window. [Citation Graph (, )][DBLP]


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