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Florence d'Alché-Buc: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Bruno-Edouard Perrin, Liva Ralaivola, Aurélien Mazurie, Samuele Bottani, Jacques Mallet, Florence d'Alché-Buc
    Gene networks inference using dynamic Bayesian networks. [Citation Graph (0, 0)][DBLP]
    ECCB, 2003, pp:138-148 [Conf]
  2. Marie-Jeanne Lesot, Florence d'Alché-Buc, George Siolas
    Evaluation of Topographic Clustering and Its Kernelization. [Citation Graph (0, 0)][DBLP]
    ECML, 2003, pp:265-276 [Conf]
  3. Olivier Gérard, Jean-Noël Patillon, Florence d'Alché-Buc
    Neural Network Adaptive Modeling of Battery Discharge Behavior. [Citation Graph (0, 0)][DBLP]
    ICANN, 1997, pp:1095-1100 [Conf]
  4. Yves Grandvalet, Florence d'Alché-Buc, Christophe Ambroise
    Boosting Mixture Models for Semi-supervised Learning. [Citation Graph (0, 0)][DBLP]
    ICANN, 2001, pp:41-48 [Conf]
  5. Yann Guermeur, Florence d'Alché-Buc, Patrick Gallinari
    Optimal Linear Regression on Classifier Outputs. [Citation Graph (0, 0)][DBLP]
    ICANN, 1997, pp:481-486 [Conf]
  6. Liva Ralaivola, Florence d'Alché-Buc
    Incremental Support Vector Machine Learning: A Local Approach. [Citation Graph (0, 0)][DBLP]
    ICANN, 2001, pp:322-330 [Conf]
  7. George Siolas, Florence d'Alché-Buc
    Mixtures of Probabilistic PCAs and Fisher Kernels for Word and Document Modeling. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:769-776 [Conf]
  8. Pierre Geurts, Louis Wehenkel, Florence d'Alché-Buc
    Kernelizing the output of tree-based methods. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:345-352 [Conf]
  9. Georges Siolas, Florence d'Alché-Buc
    Support Vector Machines Based on a Semantic Kernel for Text Categorization. [Citation Graph (0, 0)][DBLP]
    IJCNN (5), 2000, pp:205-209 [Conf]
  10. Liva Ralaivola, Florence d'Alché-Buc
    Dynamical Modeling with Kernels for Nonlinear Time Series Prediction. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  11. Florence d'Alché-Buc, Yves Grandvalet, Christophe Ambroise
    Semi-supervised MarginBoost. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:553-560 [Conf]
  12. Florence d'Alché-Buc, Vincent Andrés, Jean-Pierre Nadal
    Rule Extraction with Fuzzy Neural Network. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 1994, v:5, n:1, pp:1-11 [Journal]
  13. Florence d'Alché-Buc, Didier Zwierski, Jean-Pierre Nadal
    Trio Learning: A New Strategy for Building Hybrid Neural Trees. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 1994, v:5, n:4, pp:259-274 [Journal]
  14. Pierre Geurts, Louis Wehenkel, Florence d'Alché-Buc
    Gradient boosting for kernelized output spaces. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:289-296 [Conf]
  15. Cédric Auliac, Florence d'Alché-Buc, Vincent Frouin
    Learning Transcriptional Regulatory Networks with Evolutionary Algorithms Enhanced with Niching. [Citation Graph (0, 0)][DBLP]
    WILF, 2007, pp:612-619 [Conf]

  16. Flow-Based Bayesian Estimation of Nonlinear Differential Equations for Modeling Biological Networks. [Citation Graph (, )][DBLP]


  17. Estimating parameters and hidden variables in non-linear state-space models based on ODEs for biological networks inference. [Citation Graph (, )][DBLP]


  18. CycSim - an online tool for exploring and experimenting with genome-scale metabolic models. [Citation Graph (, )][DBLP]


  19. Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset. [Citation Graph (, )][DBLP]


  20. Inferring biological networks with output kernel trees. [Citation Graph (, )][DBLP]


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