Nombre de documents

32

CV de Christophe Ambroise


Chapitre d'ouvrage2 documents

  • Pierre Latouche, Etienne Birmelé, Christophe Ambroise. Overlapping clustering methods for networks. Edoardo M. Airoldi, David Blei, Elena A. Erosheva, Stephen E. Fienberg. Chapman and Hall/CRC. Handbook of Mixed Membership Models and Their Applications, Chapman and Hall/CRC, in press, 2014. <hal-00984395>
  • Pierre Latouche, Etienne Birmelé, Christophe Ambroise. Bayesian methods for graph clustering. Andreas Fink, Berthold Lausen, Wilfried Seidel and Alfred Ultsch. Advances in Data Analysis, Data Handling and Business Intelligence, Springer, pp.229-239, 2009, Studies in Classification, Data Analysis, and Knowledge Organization, <10.1007/978-3-642-01044-6>. <hal-00629294>

Article dans une revue14 documents

  • Virginie Stanislas, Cyril Dalmasso, Christophe Ambroise. Eigen-Epistasis for detecting Gene-Gene interactions. BMC Bioinformatics, BioMed Central, 2017, 18, pp.54. <hal-01275624v6>
  • Jean-Michel Bécu, Yves Grandvalet, Christophe Ambroise, Cyril Dalmasso. Beyond support in two-stage variable selection. Statistics and Computing, Springer Verlag (Germany), 2016, 26, pp.1-11. <10.1007/s11222-015-9614-1>. <hal-01246066>
  • Alia Dehman, Christophe Ambroise, Pierre Neuvial. Performance of a blockwise approach in variable selection using linkage disequilibrium information. BMC Bioinformatics, BioMed Central, 2015, pp.14. <10.1186/s12859-015-0556-6>. <hal-01193074>
  • Pierre Latouche, Etienne Birmelé, Christophe Ambroise. Model Selection in Overlapping Stochastic Block Models. Electronic journal of statistics , Shaker Heights, OH : Institute of Mathematical Statistics, 2014, 8, pp.762-794. <hal-00990277>
  • Christophe Ambroise, Catherine Matias. New consistent and asymptotically normal parameter estimates for random-graph mixture models. Journal of the Royal Statistical Society: Series B, Royal Statistical Society, 2012, 74, <10.1111/j.1467-9868.2011.01009.x>. <hal-00647817>
  • Pierre Latouche, Etienne Birmele, Christophe Ambroise. Variational Bayesian Inference and Complexity Control for Stochastic Block Models. Statistical Modelling, SAGE Publications, 2012, 12 (1), pp.93-115. <hal-00624536>
  • Pierre Latouche, Etienne Birmelé, Christophe Ambroise. Overlapping stochastic block models with application to the French political blogosphere. Annals Of Applied Statistics, Institute Mathematical Statistics, 2011, 5 (1), pp.309-336. <hal-00624538>
  • Julien Chiquet, Yves Grandvalet, Christophe Ambroise. Inferring Multiple Graphical Structures. Statistics and Computing, Springer Verlag (Germany), 2011, 21 (4), pp.537--553. <hal-00660169>
  • Julien Chiquet, Alexander Smith, Gilles Grasseau, Catherine Matias, Christophe Ambroise. SIMoNe: Statistical Inference for MOdular NEtworks.. Bioinformatics -Oxford-, undefined or unknown publisher, 2009, 25 (3), pp.417-8. <10.1093/bioinformatics/btn637>. <hal-00592218>
  • Christophe Ambroise, Julien Chiquet, Catherine Matias. Inferring sparse Gaussian graphical models with latent structure. Electronic journal of statistics , Shaker Heights, OH : Institute of Mathematical Statistics, 2009, 3, pp.205-238. <10.1214/08-EJS314>. <hal-00592201>
  • Christophe Ambroise, Julien Chiquet, Catherine Matias. Inferring sparse Gaussian graphical models with latent structure. Electronic journal of statistics , Shaker Heights, OH : Institute of Mathematical Statistics, 2009, <10.1214/08-EJS314>. <inria-00591491>
  • Etienne Birmele, Mohamed Elati, Céline Rouveirol, Christophe Ambroise. Identification of functional modules based on transcriptional regulation structure. BMC Proceedings, BioMed Central, 2008, 2 (4), pp.S4. <hal-00730904>
  • Marta Avalos, Yves Grandvalet, Christophe Ambroise. Parsimonious Additive Models. Computational Statistics and Data Analysis, Elsevier, 2007, 51 (6), pp.2851-2870. <10.1016/j.csda.2006.10.007>. <inserm-00149798>
  • Marta Avalos, Yves Grandvalet, Christophe Ambroise. Discrimination par modèles additifs parcimonieux : Modèles additifs parcimonieux. Revue dÍntelligence Artificielle, 2005, 19 (4-5), pp.661-682. <inserm-00149790>

Communication dans un congrès14 documents

  • Christophe Ambroise, Julien Chiquet, Marie Szafranski. A greedy great approach to learn with complementary structured datasets. Greed Is Great ICML Workshop, Jul 2015, Lille, France. <hal-01246419>
  • Jean-Michel Bécu, Yves Grandvalet, Christophe Ambroise, Cédric Dalmasso. Significance testing for variable selection in high-dimension. Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), Aug 2015, Niagara Falls, Canada. IEEE, pp.1-8, 2015, IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). <http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7300313&tag=1>. <10.1109/CIBCB.2015.7300313>. <hal-01313310>
  • Julien Chiquet, Yves Grandvalet, Christophe Ambroise. Inférence jointe de la structure de modèles graphiques gaussiens. CAp'2010, May 2010, France. pp.217-232, 2010. <hal-00936741>
  • Pierre Latouche, Etienne Birmelé, Christophe Ambroise. Modèles de graphe aléatoire à classes chevauchantes pour l'analyse des réseaux. 42èmes Journées de Statistique, 2010, Marseille, France, France. 2010. <inria-00494820>
  • Pierre Latouche, Etienne Birmelé, Christophe Ambroise. Uncovering overlapping clusters in biological networks. Journées Ouvertes en Biologie, Informatique et Mathématiques (JOBIM), Jun 2009, Nantes, France. pp.28, 2009. <hal-00629321>
  • Pierre Latouche, Etienne Birmelé, Christophe Ambroise. A latent logistic model to uncover overlapping clusters in networks. Atelier AGS (Apprentissage et Graphes pour les Systèmes complexes), May 2009, Hammamet, Tunisia. pp.3-8, 2009. <hal-00629310>
  • Allou Samé, Gérard Govaert, Christophe Ambroise. Les modèles de mélange pour la classification de données massives en temps réel. 41èmes Journées de Statistique, SFdS, Bordeaux, 2009, Bordeaux, France, France. 2009. <inria-00386796>
  • Marta Avalos, Yves Grandvalet, Christophe Ambroise. Pénalisation l1 pour les MAG. 2005, Université de Pau; SFdS, pp.25.1, 2005. <inserm-00149856>
  • Marta Avalos, Yves Grandvalet, Christophe Ambroise. Model selection via penalization in the additive Cox model. The 3rd world conference on Computational Statistics & Data Analysis, 2005, Limassol, Cyprus. International Association for Statistical Computing; University of Cyprus, pp.45, 2005. <inserm-00149852>
  • Marta Avalos, Yves Grandvalet, Christophe Ambroise. Penalized additive logistic regression for cardiovascular risk prediction. Auget; Balakrishnan; Mesbah; Molenberghs. 2004, Université de Nantes, pp.301, 2004. <inserm-00149854>
  • Marta Avalos, Yves Grandvalet, Christophe Ambroise. Généralisation du lasso aux modèles additifs. 2004, Université de Montpellier II; Agro.M; SFdS, pp.83, 2004. <inserm-00149858>
  • Philippe-Henri Gosselin, Micheline Najjar, Matthieu Cord, Christophe Ambroise. Discriminative Classification vs Modeling Methods in CBIR. IEEE International Conference on Advanced Concepts for Intelligent Vision Systems, Sep 2004, Belgium. pp.1, 2004. <hal-00520316>
  • Hani Hamdan, Gérard Govaert, Christophe Ambroise, Catherine Hervé. Mixture model approach for acoustic emission control of pressure equipment. 5th International Conference on Acoustical and Vibratory Surveillance Methods and Diagnostic Techniques, Oct 2004, Senlis, France. pp.1-10. <hal-01377401>
  • Marta Avalos, Yves Grandvalet, Christophe Ambroise. Regularization methods for additive models. M R Berthold, H J Lenz et al. 2003, LNCS Springer, pp.509-520, 2003. <inserm-00149855>

Rapport1 document

  • Serge Antoine Séguret, Christophe Ambroise, Michel Schmitt. Seismic data study.- Rapport d'avancement no. 2,. 1996. <hal-00777229>

Pré-publication, Document de travail1 document

  • Philippe-Henri Gosselin, Micheline Najjar, Matthieu Cord, Christophe Ambroise, Sylvie Philipp-Foliguet. Méthodes d'Apprentissage pour la Recherche d'Images par le Contenu.. 2004. <hal-00520277>