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Marc Sebban: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Marc Sebban, Anne M. Landraud
    Strings Clustering and Statistical Validation of Clusters. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 1998, pp:298-309 [Conf]
  2. Marc Sebban, Richard Nock
    Identifying and Eliminating Irrelevant Instances Using Information Theory. [Citation Graph (0, 0)][DBLP]
    Canadian Conference on AI, 2000, pp:90-101 [Conf]
  3. Richard Nock, Marc Sebban
    Sharper Bounds for the Hardness of Prototype and Feature Selection. [Citation Graph (0, 0)][DBLP]
    ALT, 2000, pp:224-237 [Conf]
  4. Stéphanie Jacquemont, François Jacquenet, Marc Sebban
    Constrained Sequence Mining based on Probabilistic Finite State Automata. [Citation Graph (0, 0)][DBLP]
    CAP, 2005, pp:15-30 [Conf]
  5. Marc Bernard, Amaury Habrard, Marc Sebban
    Learning Stochastic Tree Edit Distance. [Citation Graph (0, 0)][DBLP]
    ECML, 2006, pp:42-53 [Conf]
  6. Amaury Habrard, Marc Bernard, Marc Sebban
    Improvement of the State Merging Rule on Noisy Data in Probabilistic Grammatical Inference. [Citation Graph (0, 0)][DBLP]
    ECML, 2003, pp:169-180 [Conf]
  7. Marc Sebban, Henri-Maxime Suchier
    On Boosting Improvement: Error Reduction and Convergence Speed-Up. [Citation Graph (0, 0)][DBLP]
    ECML, 2003, pp:349-360 [Conf]
  8. Franck Thollard, Marc Sebban, Philippe Ézéquel
    Boosting Density Function Estimators. [Citation Graph (0, 0)][DBLP]
    ECML, 2002, pp:431-443 [Conf]
  9. Richard Nock, Marc Sebban, Pascal Jabby
    A Symmetric Nearest Neighbor Learning Rule. [Citation Graph (0, 0)][DBLP]
    EWCBR, 2000, pp:222-233 [Conf]
  10. Amaury Habrard, Marc Bernard, Marc Sebban
    Correction of Uniformly Noisy Distributions to Improve Probabilistic Grammatical Inference Algorithms. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2005, pp:493-498 [Conf]
  11. Richard Nock, Marc Sebban
    A Boosting-Based Prototype Weighting and Selection Scheme. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2000, pp:71-75 [Conf]
  12. Marc Sebban
    Prototype Selection from Homogeneous Subsets by a Monte Carlo Sampling. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 1998, pp:250-253 [Conf]
  13. Marc Sebban, Richard Nock
    Improvement of Nearest-Neighbor Classifiers via Support Vector Machines. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2001, pp:113-117 [Conf]
  14. Marc Bernard, Jean-Christophe Janodet, Marc Sebban
    A Discriminative Model of Stochastic Edit Distance in the Form of a Conditional Transducer. [Citation Graph (0, 0)][DBLP]
    ICGI, 2006, pp:240-252 [Conf]
  15. Jean-Christophe Janodet, Richard Nock, Marc Sebban, Henri-Maxime Suchier
    Boosting grammatical inference with confidence oracles. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  16. Marc Sebban, Jean-Christophe Janodet
    On State Merging in Grammatical Inference: A Statistical Approach for Dealing with Noisy Data. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:688-695 [Conf]
  17. Marc Sebban, Richard Nock
    Instance Pruning as an Information Preserving Problem. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:855-862 [Conf]
  18. Marc Sebban, Richard Nock, Stéphane Lallich
    Boosting Neighborhood-Based Classifiers. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:505-512 [Conf]
  19. François Jacquenet, Marc Sebban, Georges Valétudie
    Mining Decision Rules from Deterministic Finite Automata. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2004, pp:362-367 [Conf]
  20. Stéphanie Jacquemont, François Jacquenet, Marc Sebban
    Sequence Mining Without Sequences: A New Way for Privacy Preserving. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2006, pp:347-354 [Conf]
  21. Marc Sebban, Gilles Richard
    From Theoretical Learnability to Statistical Measures of the Learnable. [Citation Graph (0, 0)][DBLP]
    IDA, 1999, pp:3-14 [Conf]
  22. Richard Nock, Marc Sebban, Pascal Jappy
    Experiments on a Representation-Independent "Top-Down and Prune" Induction Scheme. [Citation Graph (0, 0)][DBLP]
    PKDD, 1999, pp:223-231 [Conf]
  23. Marc Sebban, Richard Nock
    Contribution of Dataset Reduction Techniques to Tree-Simplification and Knowledge Discovery. [Citation Graph (0, 0)][DBLP]
    PKDD, 2000, pp:44-53 [Conf]
  24. Marc Sebban, Richard Nock
    Contribution of Boosting in Wrapper Models. [Citation Graph (0, 0)][DBLP]
    PKDD, 1999, pp:214-222 [Conf]
  25. Marc Sebban, Djamel A. Zighed, S. Di Palma
    Selection and Statistical Validation of Features and Prototypes. [Citation Graph (0, 0)][DBLP]
    PKDD, 1999, pp:184-192 [Conf]
  26. José Oncina, Marc Sebban
    Using Learned Conditional Distributions as Edit Distance. [Citation Graph (0, 0)][DBLP]
    SSPR/SPR, 2006, pp:403-411 [Conf]
  27. Marc Sebban, Richard Nock
    Combining Feature and Example Pruning by Uncertainty Minimization. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:533-540 [Conf]
  28. Marc Sebban, I. Mokrousov, N. Rastogi, C. Sola
    A data-mining approach to spacer oligonucleotide typing of Mycobacterium tuberculosis. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2002, v:18, n:2, pp:235-243 [Journal]
  29. Amaury Habrard, Marc Bernard, Marc Sebban
    Detecting Irrelevant Subtrees to Improve Probabilistic Learning from Tree-structured Data. [Citation Graph (0, 0)][DBLP]
    Fundam. Inform., 2005, v:66, n:1-2, pp:103-130 [Journal]
  30. Richard Nock, Marc Sebban
    Advances in Adaptive Prototype Weighting and Selection. [Citation Graph (0, 0)][DBLP]
    International Journal on Artificial Intelligence Tools, 2001, v:10, n:1-2, pp:137-155 [Journal]
  31. Marc Sebban, Richard Nock, Jean-Hugues Chauchat, Ricco Rakotomalala
    Impact of learning set quality and size on decision tree performances. [Citation Graph (0, 0)][DBLP]
    Int. J. Comput. Syst. Signal, 2000, v:1, n:1, pp:85-105 [Journal]
  32. Richard Nock, Marc Sebban, Didier Bernard
    A Simple Locally Adaptive Nearest Neighbor Rule With Application To Pollution Forecasting. [Citation Graph (0, 0)][DBLP]
    IJPRAI, 2003, v:17, n:8, pp:1369-1382 [Journal]
  33. Sabine Rabaséda, Ricco Rakotomalala, Marc Sebban
    A Comparison of Some Contextual Discretization Methods. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 1996, v:92, n:1-4, pp:137-157 [Journal]
  34. Marc Sebban, Richard Nock, Stéphane Lallich
    Stopping Criterion for Boosting-Based Data Reduction Techniques: from Binary to Multiclass Problem. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2002, v:3, n:, pp:863-885 [Journal]
  35. José Oncina, Marc Sebban
    Learning stochastic edit distance: Application in handwritten character recognition. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 2006, v:39, n:9, pp:1575-1587 [Journal]
  36. Marc Sebban, Richard Nock
    A hybrid filter/wrapper approach of feature selection using information theory. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 2002, v:35, n:4, pp:835-846 [Journal]
  37. Richard Nock, Marc Sebban
    An improved bound on the finite-sample risk of the nearest neighbor rule. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 2001, v:22, n:3/4, pp:407-412 [Journal]
  38. Richard Nock, Marc Sebban
    A Bayesian boosting theorem. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 2001, v:22, n:3/4, pp:413-419 [Journal]
  39. Laurent Boyer 0002, Amaury Habrard, Marc Sebban
    Learning Metrics Between Tree Structured Data: Application to Image Recognition. [Citation Graph (0, 0)][DBLP]
    ECML, 2007, pp:54-66 [Conf]

  40. Learning Constrained Edit State Machines. [Citation Graph (, )][DBLP]

  41. SEDiL: Software for Edit Distance Learning. [Citation Graph (, )][DBLP]

  42. Discovering Patterns in Flows: A Privacy Preserving Approach with the ACSM Prototype. [Citation Graph (, )][DBLP]

  43. Weighted Symbols-Based Edit Distance for String-Structured Image Classification. [Citation Graph (, )][DBLP]

  44. Melody Recognition with Learned Edit Distances. [Citation Graph (, )][DBLP]

  45. Correct your text with Google. [Citation Graph (, )][DBLP]

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