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ORCIDSébastien Déjean
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- affiliation: University of Toulouse, France
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2020 – today
- 2024
[c11]Adrian-Gabriel Chifu, Sébastien Déjean, Moncef Garouani, Josiane Mothe, Diégo Ortiz, Md. Zia Ullah:
Prédictibilité de la prédiction de la performance des requêtes ? Une approche basée sur les valeurs aberrantes multivariées. CORIA 2024- [c10]Adrian-Gabriel Chifu
, Sébastien Déjean, Moncef Garouani, Josiane Mothe, Diégo Ortiz, Md. Zia Ullah:
Can We Predict QPP? An Approach Based on Multivariate Outliers. ECIR (3) 2024: 458-467 - [i4]Adrian-Gabriel Chifu, Sébastien Déjean, Moncef Garouani, Josiane Mothe, Diégo Ortiz, Md. Zia Ullah:
Can we predict QPP? An approach based on multivariate outliers. CoRR abs/2402.16875 (2024) - [i3]Mitja Briscik, Gabriele Tazza, Marie-Agnès Dillies, László Vidács, Sébastien Déjean:
Supervised Multiple Kernel Learning approaches for multi-omics data integration. CoRR abs/2403.18355 (2024) - 2023
- [j14]Mitja Briscik, Marie-Agnès Dillies, Sébastien Déjean:
Improvement of variables interpretability in kernel PCA. BMC Bioinform. 24(1): 282 (2023) - [j13]Élise Maigné, Céline Noirot, Julien Henry, Yaa Adu Kesewaah, Ludovic Badin, Sébastien Déjean, Camille Guilmineau, Arielle Krebs, Fanny Mathevet, Audrey Segalini, Laurent Thomassin, David Colongo, Christine Gaspin, Laurence Liaubet, Nathalie Vialaneix:
Asterics: a simple tool for the ExploRation and Integration of omiCS data. BMC Bioinform. 24(1): 391 (2023) - 2021
- [j12]Harold Duruflé, Merwann Selmani, Philippe Ranocha, Elisabeth Jamet, Christophe Dunand, Sébastien Déjean:
A powerful framework for an integrative study with heterogeneous omics data: from univariate statistics to multi-block analysis. Briefings Bioinform. 22(3) (2021) - 2020
- [c9]Sébastien Déjean, Radu Tudor Ionescu, Josiane Mothe, Md. Zia Ullah:
Forward and backward feature selection for query performance prediction. SAC 2020: 690-697
2010 – 2019
- 2019
- [c8]Sébastien Déjean, Josiane Mothe, Md. Zia Ullah:
Studying the Variability of System Setting Effectiveness by Data Analytics and Visualization. CLEF 2019: 62-74 - [i2]Sébastien Déjean, Radu Tudor Ionescu, Josiane Mothe, Md. Zia Ullah:
Forward and Backward Feature Selection for Query Performance Prediction. CoRR abs/1912.04107 (2019) - 2017
- [c7]Adrian-Gabriel Chifu, Sébastien Déjean, Stefano Mizzaro, Josiane Mothe:
Human-Based Query Difficulty Prediction. ECIR 2017: 343-356 - 2016
- [c6]Clémentine Scohy, Yassine Rkha Chaham, Sébastien Déjean, Josiane Mothe:
Tweet Data mining : the Cultural Microblog Contextualization Data Set. CLEF (Working Notes) 2016: 1246-1259 - 2015
- [j11]Léa Laporte, Sébastien Déjean, Josiane Mothe:
Sélection de variables en apprentissage d'ordonnancement. Évaluation des SVM pondérés. Document Numérique 18(1): 97-121 (2015) - [j10]Anthony Bigot, Sébastien Déjean, Josiane Mothe:
Learning to Choose the Best System Configuration in Information Retrieval: the Case of Repeated Queries. J. Univers. Comput. Sci. 21(13): 1726-1745 (2015) - [j9]Julie Ayter, Adrian-Gabriel Chifu, Sébastien Déjean, Cecile Desclaux, Josiane Mothe:
Statistical Analysis to Establish the Importance of Information Retrieval Parameters. J. Univers. Comput. Sci. 21(13): 1767-1789 (2015) - [i1]Léa Laporte, Rémi Flamary, Stéphane Canu, Sébastien Déjean, Josiane Mothe:
Non-convex Regularizations for Feature Selection in Ranking With Sparse SVM. CoRR abs/1507.00500 (2015) - 2014
- [j8]Anthony Bigot, Sébastien Déjean, Josiane Mothe:
Choisir la meilleure configuration d'un système de recherche d'information. Adaptation à la difficulté du besoin. Document Numérique 17(2): 125-147 (2014) - [j7]Léa Laporte, Rémi Flamary, Stéphane Canu, Sébastien Déjean, Josiane Mothe:
Nonconvex Regularizations for Feature Selection in Ranking With Sparse SVM. IEEE Trans. Neural Networks Learn. Syst. 25(6): 1118-1130 (2014) - [c5]Léa Laporte, Sébastien Déjean, Josiane Mothe:
Séparateurs à Vaste Marge pondérés en norme L2 pour la sélection de variables en apprentissage d'ordonnancement. CORIA-CIFED 2014: 321-336 - 2013
- [c4]Léa Laporte, Sébastien Déjean, Josiane Mothe:
Multiple Clicks Model for Web Search of Multi-clickable Documents. ICEIS (1) 2013: 298-303 - 2012
- [j6]Ignacio González, Kim-Anh Lê Cao, Melissa J. Davis, Sébastien Déjean:
Visualising associations between paired 'omics' data sets. BioData Min. 5: 19 (2012) - [j5]Alain Baccini, Sébastien Déjean, Laetitia Lafage, Josiane Mothe:
How many performance measures to evaluate information retrieval systems? Knowl. Inf. Syst. 30(3): 693-713 (2012) - [j4]Serge Cohen, Sébastien Déjean, Sébastien Gadat:
Adaptive sequential design for regression on multi-resolution bases. Stat. Comput. 22(3): 753-772 (2012) - [c3]Léa Laporte, Laurent Candillier, Sébastien Déjean, Josiane Mothe:
Évaluation de la pertinence dans les moteurs de recherche géoréférencés . INFORSID 2012: 281-298 - 2010
- [j3]Alain Baccini, Sébastien Déjean, Désiré Kompaoré, Josiane Mothe:
Analyse des critères d'évaluation des systèmes de recherche d'information. Tech. Sci. Informatiques 29(3): 289-308 (2010)
2000 – 2009
- 2009
- [j2]Kim-Anh Lê Cao, Ignacio González, Sébastien Déjean:
integrOmics: an R package to unravel relationships between two omics datasets. Bioinform. 25(21): 2855-2856 (2009) - 2007
- [j1]Sébastien Déjean, Pascal G. P. Martin, Alain Baccini, Philippe Besse:
Clustering Time-Series Gene Expression Data Using Smoothing Spline Derivatives. EURASIP J. Bioinform. Syst. Biol. 2007 (2007) - [c2]Désiré Kompaoré, Josiane Mothe, Alain Baccini, Sébastien Déjean:
Prédiction du SRI à utiliser en fonction des critères linguistiques de la requête. CORIA 2007: 239-254 - [c1]Désiré Kompaoré, Josiane Mothe, Alain Baccini, Sébastien Déjean:
Query clustering to decide the best system to use. RIAO 2007: 173-191
Coauthor Index
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