G. J. Mclachlan and D. Peel, Finite Mixture Models, 2000.
DOI : 10.1002/0471721182

A. Moore, Very fast EM-based mixture model clustering using multiresolution kd-trees, Advances in Neural Information Processing Systems, pp.543-549, 1999.

A. Moore and D. Pelleg, Accelerating exact kmeans algorithms with geometric reasoning, Proc. of 5th Int. Conf. on Knowledge Discovery and Data Mining, pp.277-281, 1999.

T. Kanungo, D. M. Mount, N. Netanyahu, C. Piatko, R. Silverman et al., An efficient k-means clustering algorithm: analysis and implementation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.7, pp.881-892, 2002.
DOI : 10.1109/TPAMI.2002.1017616

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.43.2981

K. Alsabti, S. Ranka, and V. Singh, An efficient k-means clustering algorithm, Proc. First Workshop High Performance Data Mining, 1998.

R. M. Neal and G. E. Hinton, A View of the Em Algorithm that Justifies Incremental, Sparse, and other Variants, Learning in Graphical Models, pp.355-368, 1998.
DOI : 10.1007/978-94-011-5014-9_12

B. G. Lindsay, The Geometry of Mixture Likelihoods: A General Theory, The Annals of Statistics, vol.11, issue.1, pp.86-94, 1983.
DOI : 10.1214/aos/1176346059

A. P. Dempster, N. M. Laird, and D. B. Rubin, Maximum likelihood from incomplete data via the EM algorithm, J. Roy. Statist. Soc. B, vol.39, pp.1-38, 1977.

J. L. Bentley, Multidimensional binary search trees used for associative searching, Communications of the ACM, vol.18, issue.9, pp.509-517, 1975.
DOI : 10.1145/361002.361007

R. F. Sproull, Refinements to nearest-neighbor searching ink-dimensional trees, Algorithmica, vol.3, issue.3, pp.579-589, 1991.
DOI : 10.1007/BF01759061

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.458.9739

S. Dasgupta, Learning mixtures of Gaussians, 40th Annual Symposium on Foundations of Computer Science (Cat. No.99CB37039), 1999.
DOI : 10.1109/SFFCS.1999.814639

N. Vlassis and A. Likas, A greedy EM algorithm for Gaussian mixture learning, Neural Processing Letters, vol.15, issue.1, pp.77-87, 2002.
DOI : 10.1023/A:1013844811137

J. J. Verbeek, N. Vlassis, B. J. Svensén, and C. K. Williams, Efficient Greedy Learning of Gaussian Mixture Models, Neural Computation, vol.35, issue.1, pp.469-485215, 1998.
DOI : 10.1214/aos/1176344374

URL : https://hal.archives-ouvertes.fr/inria-00321487

M. Titsias and A. Likas, Shared kernel models for class conditional density estimation, IEEE Transactions on Neural Networks, vol.12, issue.5, pp.987-997, 2001.
DOI : 10.1109/72.950129

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.3007