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Thierry Denoeux: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Lalla Merieme Zouhal, Thierry Denoeux
    An Adaptive k-NN Rule Based on Dempster-Shafer Theory. [Citation Graph (0, 0)][DBLP]
    CAIP, 1995, pp:310-317 [Conf]
  2. Sabrina Démotier, Thierry Denoeux, Paul Walter Schön
    Risk Assessment in Drinking Water Production Using Belief Functions. [Citation Graph (0, 0)][DBLP]
    ECSQARU, 2003, pp:319-331 [Conf]
  3. David Mercier, Benjamin Quost, Thierry Denoeux
    Contextual Discounting of Belief Functions. [Citation Graph (0, 0)][DBLP]
    ECSQARU, 2005, pp:552-562 [Conf]
  4. Simon Petit-Renaud, Thierry Denoeux
    Handling Different Forms of Uncertainty in Regression Analysis: A Fuzzy Belief Structure Approach. [Citation Graph (0, 0)][DBLP]
    ESCQARU, 1999, pp:340-351 [Conf]
  5. Michèle Rombaut, Iman Jarkass, Thierry Denoeux
    State Recognition in Discrete Dynamical Systems Using Petri Nets and Evidence Theory. [Citation Graph (0, 0)][DBLP]
    ESCQARU, 1999, pp:352-361 [Conf]
  6. Amel Ben Yaghlane, Thierry Denoeux, Khaled Mellouli
    Coarsening Approximations of Belief Functions. [Citation Graph (0, 0)][DBLP]
    ECSQARU, 2001, pp:362-373 [Conf]
  7. Patrick Vannoorenberghe, Thierry Denoeux
    Likelihood-based Vs Distance-based Evidential Classifiers. [Citation Graph (0, 0)][DBLP]
    FUZZ-IEEE, 2001, pp:320-323 [Conf]
  8. Sandro Glaucio Maquiné de Souza, Thierry Denoeux, Yves Grandvalet
    Recycling experiments for sludge monitoring in waste water treatment. [Citation Graph (0, 0)][DBLP]
    SMC (2), 2004, pp:1342-1347 [Conf]
  9. Hughes Bersini, Thierry Denoeux, Didier Dubois, Henri Prade
    In Memoriam: Philippe Smets (1938-2005). [Citation Graph (0, 0)][DBLP]
    Fuzzy Sets and Systems, 2006, v:157, n:8, pp:- [Journal]
  10. Thierry Denoeux
    R. P. Srivastava and T. J. Mock, Belief Functions in Business Decisions, in Studies in Fuzziness and Soft Computing, vol. 88, Physica-Verlag, Heidelberg (2002) ISBN 3-7908-1451-2 (345pp.) [Citation Graph (0, 0)][DBLP]
    Fuzzy Sets and Systems, 2005, v:151, n:2, pp:435-436 [Journal]
  11. Thierry Denoeux, Marie-Hélène Masson, Pierre-Alexandre Hébert
    Nonparametric rank-based statistics and significance tests for fuzzy data. [Citation Graph (0, 0)][DBLP]
    Fuzzy Sets and Systems, 2005, v:153, n:1, pp:1-28 [Journal]
  12. Thierry Denoeux, Lalla Merieme Zouhal
    Handling possibilistic labels in pattern classification using evidential reasoning. [Citation Graph (0, 0)][DBLP]
    Fuzzy Sets and Systems, 2001, v:122, n:3, pp:409-424 [Journal]
  13. Marie-Hélène Masson, Thierry Denoeux
    Multidimensional scaling of fuzzy dissimilarity data. [Citation Graph (0, 0)][DBLP]
    Fuzzy Sets and Systems, 2002, v:128, n:3, pp:339-352 [Journal]
  14. Marie-Hélène Masson, Thierry Denoeux
    Inferring a possibility distribution from empirical data. [Citation Graph (0, 0)][DBLP]
    Fuzzy Sets and Systems, 2006, v:157, n:3, pp:319-340 [Journal]
  15. Nicolas Valentin, Thierry Denoeux
    A neural network-based software sensor for coagulation control in a water treatment plant. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2001, v:5, n:1, pp:23-39 [Journal]
  16. Hughes Bersini, Thierry Denoeux, Didier Dubois, Henri Prade
    Philippe Smets (1938-2005). [Citation Graph (0, 0)][DBLP]
    Int. J. Approx. Reasoning, 2006, v:41, n:3, pp:- [Journal]
  17. Thierry Denoeux
    Constructing belief functions from sample data using multinomial confidence regions. [Citation Graph (0, 0)][DBLP]
    Int. J. Approx. Reasoning, 2006, v:42, n:3, pp:228-252 [Journal]
  18. Thierry Denoeux
    Reasoning with imprecise belief structures. [Citation Graph (0, 0)][DBLP]
    Int. J. Approx. Reasoning, 1999, v:20, n:1, pp:79-111 [Journal]
  19. Thierry Denoeux, Piero P. Bonissone
    Editorial. [Citation Graph (0, 0)][DBLP]
    Int. J. Approx. Reasoning, 2005, v:40, n:3, pp:125-126 [Journal]
  20. Thierry Denoeux, Amel Ben Yaghlane
    Approximating the combination of belief functions using the fast Mo"bius transform in a coarsened frame. [Citation Graph (0, 0)][DBLP]
    Int. J. Approx. Reasoning, 2002, v:31, n:1-2, pp:77-101 [Journal]
  21. Simon Petit-Renaud, Thierry Denoeux
    Nonparametric regression analysis of uncertain and imprecise data using belief functions. [Citation Graph (0, 0)][DBLP]
    Int. J. Approx. Reasoning, 2004, v:35, n:1, pp:1-28 [Journal]
  22. Thierry Denoeux
    Inner and Outer Approximation of Belief Structures Using a Hierarchical Clustering Approach. [Citation Graph (0, 0)][DBLP]
    International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2001, v:9, n:4, pp:437-460 [Journal]
  23. Jérémie François, Yves Grandvalet, Thierry Denoeux, Jean-Michel Roger
    Resample and combine: an approach to improving uncertainty representation in evidential pattern classification. [Citation Graph (0, 0)][DBLP]
    Information Fusion, 2003, v:4, n:2, pp:75-85 [Journal]
  24. Jérémie François, Yves Grandvalet, Thierry Denoeux, Jean-Michel Roger
    Addendum to resample and combine: an approach to improving uncertainty representation in evidential pattern classification. [Citation Graph (0, 0)][DBLP]
    Information Fusion, 2003, v:4, n:3, pp:235-236 [Journal]
  25. Thierry Denoeux, P. Rizand
    Analysis of Rainfall Forecasting using Neural Networks. [Citation Graph (0, 0)][DBLP]
    Neural Computing and Applications, 1995, v:3, n:1, pp:50-61 [Journal]
  26. Thierry Denoeux, Régis Lengellé
    Initializing back propagation networks with prototypes. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1993, v:6, n:3, pp:351-363 [Journal]
  27. Régis Lengellé, Thierry Denoeux
    Training MLPs layer by layer using an objective function for internal representations. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1996, v:9, n:1, pp:83-97 [Journal]
  28. Thierry Denoeux, Marie-Hélène Masson
    Multidimensional scaling of interval-valued dissimilarity data. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 2000, v:21, n:1, pp:83-92 [Journal]
  29. Marie-Hélène Masson, Thierry Denoeux
    Clustering interval-valued proximity data using belief functions. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 2004, v:25, n:2, pp:163-171 [Journal]
  30. Benjamin Quost, Thierry Denoeux, Marie-Hélène Masson
    Pairwise classifier combination using belief functions. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 2007, v:28, n:5, pp:644-653 [Journal]
  31. Thierry Denoeux, Marie-Hélène Masson
    Principal component analysis of fuzzy data using autoassociative neural networks. [Citation Graph (0, 0)][DBLP]
    IEEE T. Fuzzy Systems, 2004, v:12, n:3, pp:336-349 [Journal]
  32. Thierry Denoeux
    A neural network classifier based on Dempster-Shafer theory. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Systems, Man, and Cybernetics, Part A, 2000, v:30, n:2, pp:131-150 [Journal]
  33. Thierry Denoeux, Marie-Hélène Masson
    EVCLUS: evidential clustering of proximity data. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Systems, Man, and Cybernetics, Part B, 2004, v:34, n:1, pp:95-109 [Journal]
  34. Pierre-Alexandre Hébert, Marie-Hélène Masson, Thierry Denoeux
    Fuzzy multidimensional scaling. [Citation Graph (0, 0)][DBLP]
    Computational Statistics & Data Analysis, 2006, v:51, n:1, pp:335-359 [Journal]
  35. Astride Aregui, Thierry Denoeux
    Consonant Belief Function Induced by a Confidence Set of Pignistic Probabilities. [Citation Graph (0, 0)][DBLP]
    ECSQARU, 2007, pp:344-355 [Conf]
  36. Thierry Denoeux
    Pattern Recognition and Information Fusion Using Belief Functions: Some Recent Developments. [Citation Graph (0, 0)][DBLP]
    ECSQARU, 2007, pp:1- [Conf]
  37. Frédéric Pichon, Thierry Denoeux
    On Latent Belief Structures. [Citation Graph (0, 0)][DBLP]
    ECSQARU, 2007, pp:368-380 [Conf]

  38. Belief Functions and Cluster Ensembles. [Citation Graph (, )][DBLP]


  39. A New Justification of the Unnormalized Dempster's Rule of Combination from the Least Commitment Principle. [Citation Graph (, )][DBLP]


  40. Noiseless Independent Factor Analysis with Mixing Constraints in a Semi-supervised Framework. Application to Railway Device Fault Diagnosis. [Citation Graph (, )][DBLP]


  41. Evidential Multi-Label Classification Approach to Learning from Data with Imprecise Labels. [Citation Graph (, )][DBLP]


  42. Learning from data with uncertain labels by boosting credal classifiers. [Citation Graph (, )][DBLP]


  43. Theory of Belief Functions for Data Analysis and Machine Learning Applications: Review and Prospects. [Citation Graph (, )][DBLP]


  44. Multisensor data fusion for OD matrix estimation. [Citation Graph (, )][DBLP]


  45. Clustering Fuzzy Data Using the Fuzzy EM Algorithm. [Citation Graph (, )][DBLP]


  46. An Evidence-Theoretic k-Nearest Neighbor Rule for Multi-label Classification. [Citation Graph (, )][DBLP]


  47. Fuzzy Modelling of Sensor Data for the Estimation of an Origin-Destination Matrix. [Citation Graph (, )][DBLP]


  48. Mixture Model Estimation with Soft Labels. [Citation Graph (, )][DBLP]


  49. Conjunctive and disjunctive combination of belief functions induced by nondistinct bodies of evidence. [Citation Graph (, )][DBLP]


  50. Representing uncertainty on set-valued variables using belief functions. [Citation Graph (, )][DBLP]


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