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ORCIDMarc Sebban
- > Home > Persons > Marc Sebban
Publications
- 2013
[i2]Marc Sebban, Richard Nock:
Combining Feature and Prototype Pruning by Uncertainty Minimization. CoRR abs/1301.3891 (2013)- 2005
- [j10]Jean-Christophe Janodet, Richard Nock, Marc Sebban, Henri-Maxime Suchier:
Adaptation du boosting à l'inférence grammaticale via l'utilisation d'un oracle de confiance. Rev. d'Intelligence Artif. 19(4-5): 713-740 (2005) - 2004
- [c21]Jean-Christophe Janodet, Richard Nock, Marc Sebban, Henri-Maxime Suchier:
Boosting grammatical inference with confidence oracles. ICML 2004 - 2003
- [j9]Richard Nock, Marc Sebban, Didier Bernard:
A Simple Locally Adaptive Nearest Neighbor Rule With Application To Pollution Forecasting. Int. J. Pattern Recognit. Artif. Intell. 17(8): 1369-1382 (2003) - 2002
- [j7]Marc Sebban, Richard Nock, Stéphane Lallich:
Stopping Criterion for Boosting-Based Data Reduction Techniques: from Binary to Multiclass Problem. J. Mach. Learn. Res. 3: 863-885 (2002) - [j6]Marc Sebban, Richard Nock:
A hybrid filter/wrapper approach of feature selection using information theory. Pattern Recognit. 35(4): 835-846 (2002) - 2001
- [j5]Richard Nock, Marc Sebban:
Advances in Adaptive Prototype Weighting and Selection. Int. J. Artif. Intell. Tools 10(1-2): 137-155 (2001) - [j4]Richard Nock, Marc Sebban:
An improved bound on the finite-sample risk of the nearest neighbor rule. Pattern Recognit. Lett. 22(3/4): 407-412 (2001) - [j3]Richard Nock, Marc Sebban:
A Bayesian boosting theorem. Pattern Recognit. Lett. 22(3/4): 413-419 (2001) - [c15]Marc Sebban, Richard Nock:
Improvement of Nearest-Neighbor Classifiers via Support Vector Machines. FLAIRS 2001: 113-117 - [c14]Marc Sebban, Richard Nock, Stéphane Lallich:
Boosting Neighborhood-Based Classifiers. ICML 2001: 505-512 - 2000
- [j2]Marc Sebban, Richard Nock, Jean-Hugues Chauchat, Ricco Rakotomalala:
Impact of learning set quality and size on decision tree performances. Int. J. Comput. Syst. Signals 1(1): 85-105 (2000) - [c13]Marc Sebban, Richard Nock:
Identifying and Eliminating Irrelevant Instances Using Information Theory. AI 2000: 90-101 - [c12]Richard Nock, Marc Sebban:
Sharper Bounds for the Hardness of Prototype and Feature Selection. ALT 2000: 224-237 - [c11]Richard Nock, Marc Sebban, Pascal Jabby:
A Symmetric Nearest Neighbor Learning Rule. EWCBR 2000: 222-233 - [c10]Richard Nock, Marc Sebban:
A Boosting-Based Prototype Weighting and Selection Scheme. FLAIRS 2000: 71-75 - [c9]Marc Sebban, Richard Nock:
Instance Pruning as an Information Preserving Problem. ICML 2000: 855-862 - [c8]Marc Sebban, Richard Nock:
Contribution of Dataset Reduction Techniques to Tree-Simplification and Knowledge Discovery. PKDD 2000: 44-53 - [c7]Marc Sebban, Richard Nock:
Combining Feature and Example Pruning by Uncertainty Minimization. UAI 2000: 533-540 - 1999
- [c4]Marc Sebban, Richard Nock:
Contribution of Boosting in Wrapper Models. PKDD 1999: 214-222 - [c3]Richard Nock, Marc Sebban, Pascal Jappy:
Experiments on a Representation-Independent "Top-Down and Prune" Induction Scheme. PKDD 1999: 223-231
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