Automatic subspace clustering of high-dimensional data for data mining application, ACM SIGMOD International Conference on Management of Data, pp.94-105, 1998. ,
A new look at the statistical model identification, IEEE Transactions on Automatic Control, vol.19, issue.6, pp.716-723, 1974. ,
DOI : 10.1109/TAC.1974.1100705
Biomarker discovery in MALDI-TOF serum protein profiles using discrete wavelet transformation, Bioinformatics, vol.25, issue.5, pp.25643-649, 2009. ,
DOI : 10.1093/bioinformatics/btn662
The irises of the Gaspé Peninsula, Bulletin of the American Iris Society, vol.59, pp.2-5, 1935. ,
Mixtures of Factor Analyzers with Common Factor Loadings: Applications to the Clustering and Visualization of High-Dimensional Data, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.7, pp.1298-1309, 2009. ,
DOI : 10.1109/TPAMI.2009.149
Dynamic Programming, 1957. ,
Assessing a mixture model for clustering with the integrated completed likelihood, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.22, issue.7, pp.719-725, 2001. ,
DOI : 10.1109/34.865189
Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models, Computational Statistics & Data Analysis, vol.41, issue.3-4, pp.561-575, 2003. ,
DOI : 10.1016/S0167-9473(02)00163-9
GTM: The Generative Topographic Mapping, Neural Computation, vol.39, issue.1, pp.215-234, 1998. ,
DOI : 10.1007/BF01889678
A Hybrid Feature Extraction Selection Approach for High-Dimensional Non-Gaussian Data Clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.8, pp.311429-1443, 2009. ,
DOI : 10.1109/TPAMI.2008.155
High-dimensional data clustering, Computational Statistics & Data Analysis, vol.52, issue.1, pp.502-519, 2007. ,
DOI : 10.1016/j.csda.2007.02.009
URL : https://hal.archives-ouvertes.fr/inria-00548573
CANONICAL VARIATE ANALYSIS-A GENERAL MODEL FORMULATION, Australian Journal of Statistics, vol.11, issue.1, pp.86-96, 1984. ,
DOI : 10.1111/j.1467-842X.1984.tb01271.x
The SEM algorithm: a probabilistic teacher algorithm from the EM algorithm for the mixture problem, Computational Statistics Quaterly, vol.2, issue.1, pp.73-92, 1985. ,
A classification EM algorithm for clustering and two stochastic versions, Computational Statistics & Data Analysis, vol.14, issue.3, pp.315-332, 1992. ,
DOI : 10.1016/0167-9473(92)90042-E
URL : https://hal.archives-ouvertes.fr/inria-00075196
K-means Iterative Fisher (KIF) unsupervised clustering algorithm applied to image texture segmentation, Pattern Recognition, vol.35, issue.9, pp.1959-1972, 2002. ,
DOI : 10.1016/S0031-3203(01)00138-8
Adaptative dimension reduction using discriminant analysis and k-means clustering. ICML, 2007. ,
Pattern classification, 2000. ,
THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS, Annals of Eugenics, vol.59, issue.2, pp.179-188, 1936. ,
DOI : 10.1111/j.1469-1809.1936.tb02137.x
An Optimal Set of Discriminant Vectors, IEEE Transactions on Computers, vol.24, issue.3, pp.281-289, 1975. ,
DOI : 10.1109/T-C.1975.224208
MCLUST: Software for Model-Based Cluster Analysis, Journal of Classification, vol.16, issue.2, pp.297-306, 1999. ,
DOI : 10.1007/s003579900058
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.142.8930
Model-Based Clustering, Discriminant Analysis, and Density Estimation, Journal of the American Statistical Association, vol.97, issue.458, p.97, 2002. ,
DOI : 10.1198/016214502760047131
Regularized Discriminant Analysis, Journal of the American Statistical Association, vol.33, issue.405, pp.165-175, 1989. ,
DOI : 10.1080/01621459.1989.10478752
Introduction to Statistical Pattern Recognition, 1990. ,
A generalized Foley???Sammon transform based on generalized fisher discriminant criterion and its application to face recognition, Pattern Recognition Letters, vol.24, issue.1-3, pp.147-158, 2003. ,
DOI : 10.1016/S0167-8655(02)00207-6
A note on the orthonormal discriminant vector method for feature extraction, Pattern Recognition, vol.24, issue.7, pp.681-684, 1991. ,
DOI : 10.1016/0031-3203(91)90035-4
Penalized Discriminant Analysis, The Annals of Statistics, vol.23, issue.1, pp.73-102, 1995. ,
DOI : 10.1214/aos/1176324456
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.35.8378
The elements of statistical learning, 2009. ,
Generalizing discriminant analysis using the generalized singular value decomposition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.8, pp.995-1006 ,
DOI : 10.1109/TPAMI.2004.46
Data clustering: a review, ACM Computing Surveys, vol.31, issue.3, pp.264-323, 1999. ,
DOI : 10.1145/331499.331504
Face recognition based on the uncorrelated optimal discriminant vectors, Pattern Recognition, vol.10, issue.34, pp.2041-2047, 2001. ,
Principal Component Analysis, 1986. ,
DOI : 10.1007/978-1-4757-1904-8
Some results on Tchebycheffian spline functions, Journal of Mathematical Analysis and Applications, vol.33, issue.1, pp.82-95, 1971. ,
DOI : 10.1016/0022-247X(71)90184-3
Principles of Multivariate Analysis, 2003. ,
Simultaneous feature selection and clustering using mixture models, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.9, pp.1154-1166, 2004. ,
DOI : 10.1109/TPAMI.2004.71
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.142.3284
A generalized optimal set of discriminant vectors, Pattern Recognition, vol.25, issue.7, pp.731-739, 1992. ,
DOI : 10.1016/0031-3203(92)90136-7
Variable Selection for Clustering with Gaussian Mixture Models, Biometrics, vol.100, issue.3, pp.701-709, 2009. ,
DOI : 10.1111/j.1541-0420.2008.01160.x
URL : https://hal.archives-ouvertes.fr/inria-00153057
The EM algorithm and extensions, 1997. ,
Finite Mixture Models, 2000. ,
DOI : 10.1002/0471721182
Modelling high-dimensional data by mixtures of factor analyzers, Computational Statistics & Data Analysis, vol.41, issue.3-4, pp.379-388, 2003. ,
DOI : 10.1016/S0167-9473(02)00183-4
Parsimonious Gaussian mixture models, Statistics and Computing, vol.61, issue.3, pp.285-296, 2008. ,
DOI : 10.1007/s11222-008-9056-0
Heteroscedastic Factor Mixture Analysis. Statistical Modeling: An International journal (forthcoming), pp.441-460, 2010. ,
DOI : 10.1177/1471082x0901000405
Subspace clustering for high dimensional data, ACM SIGKDD Explorations Newsletter, vol.6, issue.1, pp.69-76, 1998. ,
DOI : 10.1145/1007730.1007731
Variable Selection for Model-Based Clustering, Journal of the American Statistical Association, vol.101, issue.473, pp.168-178, 2006. ,
DOI : 10.1198/016214506000000113
EM algorithms for ML factor analysis, Psychometrika, vol.34, issue.1, pp.69-76, 1982. ,
DOI : 10.1007/BF02293851
Estimating the Dimension of a Model, The Annals of Statistics, vol.6, issue.2, pp.461-464, 1978. ,
DOI : 10.1214/aos/1176344136
Probability density estimation in higher dimensions, Fifteenth Symposium in the Interface, pp.173-179, 1983. ,
Mixtures of Probabilistic Principal Component Analyzers, Neural Computation, vol.2, issue.1, pp.443-482, 1999. ,
DOI : 10.1007/BF00162527
DALASS: Variable selection in discriminant analysis via the LASSO, Computational Statistics & Data Analysis, vol.51, issue.8, pp.3718-3736, 2007. ,
DOI : 10.1016/j.csda.2006.12.046
The Curse of Dimensionality in Data Mining and Time Series Prediction, 2005. ,
DOI : 10.1007/11494669_93
Characterization of a family of algorithms for generalized discriminant analysis on undersampled problems, Journal of Machine Learning Research, vol.6, pp.483-502, 2005. ,
Discriminative k-means for clustering, Advances in Neural Information Processing Systems, pp.1649-1656, 2007. ,