Institut de Mathématiques de Luminy

BIBLIOGRAPHIE - Badih GHATTAS



Année
Publications
Files Type
  Ghattas Badih, Perera Gonzalo.
A resource-restricted learning algorithm for on-line evaluation of non-stationary data.
To appear in Statistical Analysis of networks, 2008.
  ACL
2013 Bourel Mathias, Ghattas Badih.
Aggregating density estimators: an empirical study.
Open Journal of Statistics, Vol. 3 No. 5, pp. 344--355, 2013.
PDF ACL
  Boutahar Mohamed, Ghattas Badih, Pommeret Denys.
Nonparametric comparison of several transformations of distribution functions.
Journal of Non Parametric Statistics, Volume 25, Issue 3, pages 619--633, 2013.
LINK ACL
  Fraiman Ricardo, Ghattas Badih, Svarc Marcela.
Interpretable clustering using unsupervised binary trees.
Advances of Data Analysis and Classification, Vol 7 (2), pp 125--145, 2013.
PDF ACL
  Boucekine M., Loundou A., Baumstarck K., Minaya-Flores P., Pelletier J., Ghattas Badih, Auquier P.
Using the random forest method to detect a response shift in the quality of life of multiple sclerosis patients: a cohort study.
BMC Medical Research Methodology, 13(1):20, february 2013.
PDF ACL
2012 Fellah S., Caudal D., De Paula AM., Dory-Lautrec P., Figarella-Branger D., Chinot O., Metellus P., Cozzone PJ., Confort-Gouny S., Ghattas Badih, Callot V., Girard N.
Multimodal MR imaging (diffusion, perfusion, and spectroscopy): is it possible to distinguish oligodendroglial tumor grade and 1p/19q codeletion in the pretherapeutic diagnosis?
Am. J. of Neuroradiol., 10.3174/ajnr.A3352, 6 december 2012.
PDF ACL
  Ghattas Badih, Crisci Carolina, Perera Gonzalo.
A review of machine learning algorithms and their application to ecological data.
Ecological Modeling 240, 113--122, august 2012.
PDF ACL
2011 Ghattas Badih, Pommeret Denys, Reboul Laurence, Yao Anne-Françoise.
Data driven smooth test for paired populations.
J. Statist. Plann. Inference 141, no. 1, 262--275, 2011.
science
direct
ACL
2010 Ghattas Badih, Deniau Claude.
Multivariate unsupervised discretization preserving mutual information.
Advances and Applications in Statistics, Volume 19, Issue 1, Pages 49--64, November 2010
arXiv ACL
  Ghattas Badih.
Bayesian networks over clusters.
Technical report, IML, 2010.
  AP
2009 Boutahar Mohamed, Ghattas Badih, Pommeret Denys.
Change detection in the distribution between two panels.
Technical report, Preprint, 2009.
  AP
  Ghattas Badih.
Discrétisation Multivariée non supervisée.
JDS2009, Bordeaux, 29 Mai 2009.
  ACTI
2008 Pons M., Marroni S., Machado I., Ghattas Badih, Domingo A.
Machine Learning procedures: An application to bycatch data of the marine turtles Caretta-Caretta.
Statistical Bulletin of ICCAT, 39 :1_13, 2008.
  ACL
  Ghattas Badih, Ben Ishak Anis.
Sélection de variables pour la classification binaire en grande dimension : comparaisons et application aux données de biopuces.
Société Française de Statistique, 149,3 :43–66, 2008.
  ACL
  Ben Ishak A., Delahaye N., Rihet P., Ghattas B.
Mice discrimination using feature selection methods.
In JOBIM, Marseille, 2008.
  ACTI
 

Ghattas Badih.
Discretizing microarray data for learning bayesian networks.
Technical report, IML, 2008.

  AP
  Ghattas Badih.
Boosting classification trees for multiclass problems.
Technical report, IML, 2008.
  AP
  Ghattas Badih, Piccini J., Perera Gonzalo.
Bayesian semi-supervised learning. Application to epidemiology and bioinformatics.
Technical report, IML, 2008.
  AP
2007 Ghattas Badih, Nerini D.
Classifying densities using functional regression trees: Applications in oceanology.
Computational Statistics & Data Analysis Volume 51, Issue 10, 15, pages 4984-4993, June 2007.
  ACL
2006 Lopez Fabrice, Granjeaud Samuel, Ara Takeshi, Ghattas Badih, Gautheret Daniel.
The disparate nature of intergenic polyadenylation sites.
RNA, 12: 1794 - 1801, Oct 2006.
  ACL
  Ghattas Badih, Perera Gonzalo.
From elementary martingale calculus to rigorous properties of mixtures of experts.
Bol. Asoc. Mat. Venez. 13, no. 2, 129--154, 2006.
  ACL
2005 Brion D., Calvet J.-C., Le moigne P., Ghattas Badih, Habets F.
Reconstitution par arbres de régression du rayonnement visible descendant horaire sur la France continentale, à partir de données in situ et de simulations: spatialisation et vérification sur des données indépendantes.
Note N°82 du Centre National de Recherches Météorologiques, décembre 2005.
   
2004 Ghattas B., Martin D., Thieffry D.
Prédire la transcription à partir des séquences génomiques.
Médecine/Science 20: 1036-40, 2004.
   

Thèse
(Thesis)
 
  Agrégation d'arbres de décision binaires, application à la prévision de l'ozone dans les Bouches du Rhône.
Thèse de doctorat, Université Aix-Marseille II.
page



Last update : april 25, 2013, EL.