Team mistis

Members
Overall Objectives
Scientific Foundations
Application Domains
Software
New Results
Other Grants and Activities
Dissemination
Bibliography

Bibliography

Major publications by the team in recent years

[1]
C. Amblard, S. Girard.
Estimation procedures for a semiparametric family of bivariate copulas, in: Journal of Computational and Graphical Statistics, 2005, vol. 14, no 2, p. 1–15.
[2]
J. Blanchet, F. Forbes.
Triplet Markov fields for the supervised classification of complex structure data, in: IEEE trans. on Pattern Analyis and Machine Intelligence, 2008, vol. 30(6), p. 1055–1067.
[3]
C. Bouveyron, S. Girard, C. Schmid.
High dimensional data clustering, in: Computational Statistics and Data Analysis, 2007, vol. 52, p. 502–519.
[4]
C. Bouveyron, S. Girard, C. Schmid.
High dimensional discriminant analysis, in: Communication in Statistics - Theory and Methods, 2007, vol. 36, no 14.
[5]
G. Celeux, S. Chrétien, F. Forbes, A. Mkhadri.
A Component-wise EM Algorithm for Mixtures, in: Journal of Computational and Graphical Statistics, 2001, vol. 10, p. 699–712.
[6]
G. Celeux, F. Forbes, N. Peyrard.
EM procedures using mean field-like approximations for Markov model-based image segmentation, in: Pattern Recognition, 2003, vol. 36, no 1, p. 131-144.
[7]
F. Forbes, G. Fort.
Combining Monte Carlo and Mean field like methods for inference in hidden Markov Random Fields, in: IEEE trans. PAMI, 2007, vol. 16, no 3, p. 824-837.
[8]
F. Forbes, N. Peyrard.
Hidden Markov Random Field Model Selection Criteria based on Mean Field-like Approximations, in: in IEEE trans. PAMI, August 2003, vol. 25(9), p. 1089–1101.
[9]
S. Girard.
A Hill type estimate of the Weibull tail-coefficient, in: Communication in Statistics - Theory and Methods, 2004, vol. 33, no 2, p. 205–234.
[10]
S. Girard, P. Jacob.
Extreme values and Haar series estimates of point process boundaries, in: Scandinavian Journal of Statistics, 2003, vol. 30, no 2, p. 369–384.

Publications of the year

Doctoral Dissertations and Habilitation Theses

[11]
F. Forbes.
Models and Inference for structured stochastic systems, Université Joseph-Fourier - Grenoble I, December 2010, Habilitation à Diriger des Recherches.
[12]
L. Gardes.
Contributions la théorie des valeurs extrêmes et la réduction de dimension pour la régression, Université Joseph-Fourier - Grenoble I, November 2010, Habilitation à Diriger des Recherches.
http://hal.inria.fr/tel-00540747/en
[13]
V. Khalidov.
Conjugate mixture models for the modelling of visual and auditory perception, Université Joseph-Fourier - Grenoble I, October 2010.
[14]
A. Lekina.
Estimation non paramétrique des quantiles extrêmes conditionnels, Université Joseph-Fourier - Grenoble I, October 2010.
http://hal.inria.fr/tel-00529476/en

Articles in International Peer-Reviewed Journal

[15]
A. Daouia, L. Gardes, S. Girard, A. Lekina.
Kernel estimators of extreme level curves, in: Test, 2010, to appear.
[16]
L. Gardes, S. Girard.
Conditional extremes from heavy-tailed distributions: An application to the estimation of extreme rainfall return levels, in: Extremes, 2010, vol. 13, no 2, p. 177–204.
[17]
L. Gardes, S. Girard, A. Guillou.
Weibull tail-distributions revisited: a new look at some tail estimators, in: Journal of Statistical Planning and Inference, 2010, vol. 141, no 1, p. 429–444.
[18]
L. Gardes, S. Girard, A. Lekina.
Functional nonparametric estimation of conditional extreme quantiles, in: Journal of Multivariate Analysis, 2010, vol. 101, p. 419-433.
http://hal.inria.fr/hal-00289996/en
[19]
R. Horaud, F. Forbes, M. Yguel, G. Dewaele, J. Zhang.
Rigid and Articulated Point Registration with Expectation Conditional Maximization, in: IEEE Trans. on Pattern Analysis and Machine Intelligence, 2010, To appear.
[20]
J. Jacques, C. Bouveyron, S. Girard, O. Devos, L. Duponchel, C. Ruckebusch.
Gaussian mixture models for the classification of high-dimensional vibrational spectroscopy data, in: Journal of Chemometrics, 2010, to appear.
[21]
V. Khalidov, F. Forbes, R. Horaud.
Conjugate Mixture Models for Clustering Multimodal Data, in: Neural Computation, 2011, vol. 23, no 2, p. 517-557.
[22]
M.-J. Martinez, B. Durand, D. Calavas, C. Ducrot.
Methodological approach for substantiating disease freedom in a small heterogeneous population. Application to ovine scrapie, a disease with a strong genetic susceptibility, in: Preventive Veterinary Medicine, 2010, vol. 95, p. 108–114.
[23]
L. Risser, T. Vincent, F. Forbes, J. Idier, P. Ciuciu.
Min-max extrapolation scheme for fast estimation of 3D Potts field partition functions. Application to the joint detection-estimation of brain activity in fMRI, in: Special issue of Journal of Signal Processing Systems, 2010.

International Peer-Reviewed Conference/Proceedings

[24]
C. Bouveyron, G. Celeux, S. Girard.
Intrinsic Dimension Estimation by Maximum Likelihood in Probabilistic PCA, in: 73rd Annual Meeting of the Institute of Mathematical Statistics, Gothenburg, Sweden, 2010.
[25]
F. Forbes, S. Doyle, D. Garcia-Lorenzo, C. Barillot, M. Dojat.
A Weighted Multi-Sequence Markov Model For Brain Lesion Segmentation, in: 13th International Conference on Artificial Intelligence and Statistics (AISTATS10), Sardinia, Italy, 13-15 May 2010.
[26]
F. Forbes, S. Doyle, D. Garcia-Lorenzo, C. Barillot, M. Dojat.
Adaptive weighted fusion of multiple MR sequences for brain lesion segmentation, in: IEEE International Symposium on Biomedical Imaging (ISBI), Rotterdam, The Netherlands, 14-17 April 2010.
[27]
R. Narasimha, E. Arnaud, F. Forbes, R. Horaud.
Disparity and normal estimation through alternating maximization, in: international conference on image processing (ICIP), Hong-Kong Honk Kong, 2010.
http://hal.inria.fr/inria-00517864/en
[28]
L. Risser, T. Vincent, F. Forbes, J. Idier, P. Ciuciu.
How to deal with brain deactivations in the joint detection-estimation framework?, in: Human Brain Mapping (HBM) meeting, Barcelone, Spain, 2010.

National Peer-Reviewed Conference/Proceedings

[29]
D. Abrial, L. Azizi, M. Charras-Garrido, F. Forbes.
Approche variationnelle pour la cartographie spatio-temporelle du risque en épidémiologie l'aide de champs de Markov cachés, in: 42èmes Journées de Statistique, France Marseille, France, 2010.
[30]
A. Daouia, L. Gardes, S. Girard, A. Lekina.
Estimation de courbes de niveaux extrêmes pour des lois à queues lourdes, in: 42èmes Journées de Statistique, France Marseille, France, 2010.
http://hal.inria.fr/inria-00494684/en
[31]
M. Vignes, J. Blanchet, D. Leroux, F. Forbes.
Clustering of incomplete, high dimensional and dependent biological data with SpaCEM3, in: Journee satellite MODGRAPH 2010 de JOBIM, Montpellier, France, 2010.

Workshops without Proceedings

[32]
J. Carreau, S. Girard, E. Ursu.
Spatial kernel interpolation for annual rainfall maxima, in: NICDS Workshop on Statistical Methods for Geographic and Spatial Data in the Management of Natural Resources, Montréal, Canada, mars 2010.
[33]
J. Carreau, S. Girard, E. Ursu.
Spatial kernel interpolation for annual rainfall maxima, in: Workshop on metrics and methodologies of estimation of extreme climate events, UNESCO headquarters, Paris, septembre 2010.
[34]
S. Girard.
On the regularization of the Sliced Inverse Regression, in: Workshop on Challenging problems in Statistical Learning, Paris, janvier 2010.
[35]
J. Hinde, S. de Freitas, M.-J. Martinez, C. Demetrio, G. Papageorgiou.
Random effects in cumulative mortality models, in: XXVth International Biometric Conference, Florianópolis, Brazil, December 2010.
[36]
J. Hinde, S. de Freitas, M.-J. Martinez, C. Demetrio, G. Papageorgiou.
Random effects in cumulative mortality models, in: The 2010 Conference of Applied Statistics in Ireland, Portrush, Northern Ireland, May 2010.

Scientific Books (or Scientific Book chapters)

[37]
A. Daouia, L. Gardes, S. Girard.
Nadaraya's estimates for large quantiles and free disposal support curves, in: Exploring research frontiers in contemporary statistics and econometrics - Festschrift in honor of L. Simar, I. V. Keilegom, P. Wilson (editors), Springer, 2010, to appear.
[38]
B. Scherrer, F. Forbes, C. Garbay, M. Dojat.
A joint Bayesian framework for MR brain scan tissue and structure segmentation based on distributed Markovian agents, in: Computational Intelligence in Healthcare, I. Bichindaritz, L. Jain (editors), Springer-Verlag, Berlin, 2010, To appear.

Other Publications

[39]
L. Bergé, C. Bouveyron, S. Girard.
HDclassif: an R Package for Model-Based Clustering and Discriminant Analysis of High-Dimensional Data, 2010.
http://hal.inria.fr/hal-00541203/en
[40]
C. Bouveyron, G. Celeux, S. Girard.
Intrinsic Dimension Estimation by Maximum Likelihood in Probabilistic PCA, 2010.
http://hal.inria.fr/hal-00440372/en
[41]
V. Ciriza, L. Donini, J.-B. Durand, S. Girard.
Optimal timeouts for power management under renewal or hidden Markov processes for requests, 2010.
http://hal.archives-ouvertes.fr/hal-00412509/en/
[42]
S. Girard, A. Guillou, G. Stupfler.
Frontier estimation with kernel regression on high order moments, 2010.
http://hal.inria.fr/hal-00499369/en

References in notes

[43]
C. Biernacki, G. Celeux, G. Govaert, F. Langrognet.
Model-Based Cluster and Discriminant Analysis with the MIXMOD Software, in: Computational Statistics and Data Analysis, 2006, vol. 51, no 2, p. 587–600.
[44]
C. Bouveyron.
Modélisation et classification des données de grande dimension. Application à l'analyse d'images, Université Grenoble 1, septembre 2006.
http://tel.archives-ouvertes.fr/tel-00109047
[45]
C. Chen, F. Forbes, O. Francois.
FASTRUCT: Model-based clustering made faster, in: Molecular Ecology Notes, 2006, vol. 6, p. 980–983.
[46]
G. Dewaele, F. Devernay, R. Horaud, F. Forbes.
The alignment between 3D-data and articulated shapes with bending surfaces, in: European Conf. Computer Vision, Lecture notes in Computer Science, 2006, no 3, p. 578-591.
[47]
P. Embrechts, C. Klüppelberg, T. Mikosh.
Modelling Extremal Events, Applications of Mathematics, Springer-Verlag, 1997, vol. 33.
[48]
F. Ferraty, P. Vieu.
Nonparametric Functional Data Analysis: Theory and Practice, Springer Series in Statistics, Springer, 2006.
[49]
O. Francois, S. Ancelet, G. Guillot.
Bayesian clustering using Hidden Markov Random Fields in spatial genetics, in: Genetics, 2006, p. 805–816.
[50]
L. Gardes.
Estimation d'une fonction quantile extrême, Université Montpellier 2, october 2003.
[51]
M. Garrido.
Modélisation des événements rares et estimation des quantiles extrêmes, méthodes de sélection de modèles pour les queues de distribution, Université Grenoble 1, juin 2002.
http://mistis.inrialpes.fr/people/girard/Fichiers/theseGarrido.pdf
[52]
S. Girard.
Construction et apprentissage statistique de modèles auto-associatifs non-linéaires. Application à l'identification d'objets déformables en radiographie. Modélisation et classification, Université de Cery-Pontoise, octobre 1996.
[53]
Y. Goegebeur, J. Beirlant, T. de Wet.
Kernel estimators for the second order parameter in extreme value statistics, in: Journal of Statistical Planning and Inference, 2010, vol. 140, no 9, p. 2632–2652.
[54]
M. Gomes, L. de Haan, L. Peng.
Semi-parametric Estimation of the Second Order Parameter in Statistics of Extremes, in: Extremes, 2002, vol. 5, no 4, p. 387–414.
[55]
K. Li.
Sliced inverse regression for dimension reduction, in: Journal of the American Statistical Association, 1991, vol. 86, p. 316–327.
[56]
S. Makni, J. Idier, T. Vincent, B. Thirion, G. Dehaene-Lambertz, P. Ciuciu.
A fully Bayesian approach to the parcel-based detection-estimation of brain activity in fMRI., in: NeuroImage, 07 2008, vol. 41, no 3, p. 941-69. [ DOI : 10.1016/j.neuroimage.2008.02.017 ]
http://hal-cea.archives-ouvertes.fr/cea-00333624/en/
[57]
R. Nelsen.
An introduction to copulas, Lecture Notes in Statistics, Springer-Verlag, New-York, 1999, vol. 139.
[58]
J. Pritchard, M. Stephens, P. Donnelly.
Inference of Population Structure Using Multilocus Genotype Data, in: Genetics, 2000, vol. 155, p. 945–959.
[59]
M. Seghier, A. Ramlackhansingh, J. Crinion, A. Leff, C. J. Price.
Lesion identification using unified segmentation-normalisation models and fuzzy clustering, in: Neuroimage, 2008, vol. 41, p. 1253-1266.
[60]
K. Van Leemput, F. Maes, D. Vandermeulen, A. Colchester, P. Suetens.
Automated segmentation of Multiple Sclerosis Lesions by model outlier detection, in: IEEE trans. Med. Ima., 2001, vol. 20, no 8, p. 677-688.

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