Communications publiées lors de congrès ou colloques nationaux et internationaux (64)
  1. 38. Birattari, M., Bontempi, G., & Bersini, H. (1998). Local learning for data analysis. Benelearn’98: Proceedings of the 8th Belgian-Dutch Conference on Machine Learning (pp. 55-61) (1998: ATO-DLO, Wageningen, The Netherlands).
  2. 39. Bontempi, G., Birattari, M., & Bersini, H. (1998). Lazy learning for iterated time-series prediction. Proceedings of the International Workshop on Advanced Black-Box Techniques for Nonlinear Modeling with Time-Series Prediction Modeling (pp. 62-68) (July 8-10, 1998: Katholieke Universiteit Leuven, Belgium).
  3. 40. Bontempi, G., Birattari, M., & Bersini, H. (1998). Local learning for nonlinear control. In H. J. C. Huijberts, A. J. Van der Schaft, & J. M. A. Scherpen (Eds.), Nonlinear control systems design symposium 1998: a proceedings volume from the 4th IFAC Symposium: Vol. 2 (pp. 360-365) Oxford ; New York: Published for the International Federation of Automatic Control by Pergamon.
  4. 41. Matthys, B., Falkenauer, E., Delchambre, A., Gilson, H., Schoetter, C., Robert, F., & Bersini, H. (1998). Une solution pour la surinformation du Web : la collaboration entre personnes. Actes du colloque international NTICF'98: Nouvelles Technologies de l'Information et de la Communication pour les Formations d'ingénieurs et dans l'industrie (xx/11/1998: Rouen, France)
  5. 42. Chatenet, N., & Bersini, H. (1997). Economical reinforcement learning for non stationary problems. In Artificial Neural Networks — ICANN'97 (pp. 283-288). (Lecture notes in computer science, 1327). Springer.
  6. 43. Bersini, H., & Bontempi, G. (1997). Fuzzy models viewed as multi-expert networks. In IFSA'97 Prague: proceedings seventh International Fuzzy Systems Association World Congress: Vol. 2 (pp. 354-359) Prague: Academia.
  7. 44. Bersini, H., & Bontempi, G. (1997). Now comes the time to defuzzify neuro-fuzzy models. In Intelligent components and instruments for control applications 1997 (SICICA '97): a proceedings volume from the 3rd IFAC Symposium (pp. 53-58) Oxford ; Tarrytown, N.Y., USA: Pergamon.
  8. 45. Bontempi, G., & Bersini, H. (1997). Identification of a sensor model with hybrid neuro-fuzzy methods. Proceedings of the 1997 International Conference on Engineering Applications of Neural Networks (EANN '97): Neural Networks in Engineering systems (pp. 325-328) International Conference on Engineering Applications of Neural Networks(Stockolm, Sweden).
  9. 46. Bersini, H., Birattari, M., & Bontempi, G. (1997). Combining Dynamic Programming and Neurocontrol: Some Basic Issues. Third European Workshop on Reinforcement Learning (October 13-14: Rennes, France)
  10. 47. Bersini, H., Dorigo, M., Langerman, S., Seront, G., & Gambardella, L. M. (1996). Results of the First International Contest on Evolutionary Optimisation. In Proceedings of IEEE International Conference on Evolutionary Computation, ICEC'96 (pp. 611-615) Piscataway, N.J.: IEEE Press.
  11. 48. 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) .
  12. 49. Bersini, H., Bontempi, G., & Decaestecker, C. (1995). Comparing RBF and Fuzzy Inference Systems on theoretical and practical basis. In Proc. ICANN'95 (Int. Conf. on Artificial Neural Networks) (pp. pp 169-174). (EC2 & Cie). F. Fogelman-Soulié and P. Gallinary (eds).
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