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Sébastien Déjean
Person information
- affiliation: University of Toulouse, France
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2020 – today
- 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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last updated on 2024-06-25 20:57 CEST by the dblp team
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