Papers published in national and international conferences or symposium proceedings (37)
  1. 23. Decaestecker, C., & Saerens, M. (1995). Comparisons of different RBF networks for pattern classification. In F. Fogelman-Soulié & P. Gallinary (Eds.), Industrial applications of neural networks (pp. 591-596) Singapore: World Scientific.
  2. 24. Van de Merckt, T., & Decaestecker, C. (1995). Multiple-Knowledge Representation in Concept Learning. In N. Lavrač & S. Wrobel (Eds.), Machine Learning: ECML-95 (pp. 200 - 217). (Lecture Notes in Artificial Intelligence, 912). Berlin, Heidelberg: Springer Verlag.
  3. 25. Bersini, H., Bontempi, G., & Decaestecker, C. (1995). Towards Neuro-Fuzzy Defuzzification in Benelearn '95. In Proceedings of the 5th Belgian-Dutch Conference on Machine Learning (pp. 91-98) .
  4. 26. Bersini, H., Bontempi, G., & Decaestecker, C. (1995). Comparing RBF and fuzzy inference systems on theoretical and practical basis. In F. Fogelman-Soulié & P. Gallinari (Eds.), ICANN '95: conférence internationale sur les Réseaux de neurones artificiels: Vol. 1 (pp. 169-174) Paris: EC2 & Cie.
  5. 27. Decaestecker, C., & Van de Merckt, T. (1994). Cognitive and Semantic interpretation of a NN classifier using prototypes. In World Congress on Neural Networks: Vol. 4 (pp. 453-458) Hillsdale, N.J.: L. Erlbaum.
  6. 28. Decaestecker, C., & Van de Merckt, T. (1994). How to "secure" the decisions of a NN classifier. In The 1994 IEEE International Conference on Neural Networks: Vol. 1 (pp. 263-268) Piscataway, NJ: IEEE.
  7. 29. Decaestecker, C. (1993). Using prototypes to solve problems in neural net classifiers. In Third International Conference on Artificial Neural Networks, 1993. (pp. 195-199) IET CONFERENCE PUBLICATIONS.
  8. 30. Decaestecker, C. (1993). NNP: a neural net classifier using prototypes. In 1993 IEEE International Conference on Neural Networks: Vol. 2 (pp. 822-824) New York: IEEE. doi:10.1109/ICNN.1993.298664
  9. 31. Decaestecker, C. (1991). Statistical Strategies in Incremental Conceptual Classification. In R. Gutiérrez & M. J. Valderrama (Eds.), Applied stochastic models and data analysis : proceedings of the Fifth International Symposium on ASMDA (pp. 150-161). (World Scientific). Singapore: World Scientific.
  10. 32. Decaestecker, C. (1991). Incremental Classification, a Multidisciplinary Viewpoint. In E. Diday & Y. Lechevallier (Eds.), Symbolic-numeric data analysis and learning: proceedings of the conference (pp. 283-285) New York: Nova Science Publishers.
  11. 33. Decaestecker, C. (1991). Description Contrasting in Incremental Concept Formation. In Y. Kodratoff (Ed.), Machine Learning–EWSL-91 (pp. 220-233) Berlin, Heidelberg, New York: Springer-Verlag.
  12. 34. Decaestecker, C. (1990). Formation de concepts en intelligence artificielle: Comparaison avec l'analyse relationnelle. In Proceedings of the XXIIe Journées de Statistiques (pp. 175-177) .
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