S. Delattre, S. Graf, H. Luschgy, and G. Pagès, Quantization of probability distributions under norm-based distortion measures, Statistics & Decisions, vol.22, issue.4/2004, pp.261-282, 2004.
DOI : 10.1524/stnd.22.4.261.64314

URL : https://hal.archives-ouvertes.fr/hal-00003057

J. C. Fort and G. Pagès, Asymptotics of optimal quantizers for some scalar distributions, Journal of Computational and Applied Mathematics, vol.146, issue.2, pp.253-275, 2002.
DOI : 10.1016/S0377-0427(02)00359-X

J. H. Friedman, J. L. Bentley, and R. A. Finkel, An Algorithm for Finding Best Matches in Logarithmic Expected Time, ACM Transactions on Mathematical Software, vol.3, issue.3, pp.209-226, 1977.
DOI : 10.1145/355744.355745

S. Graf and H. Luschgy, Foundations of Quantization for Probability Distributions, Lecture Notes in Mathematics, vol.1730, 2000.
DOI : 10.1007/BFb0103945

S. Graf, H. Luschgy, and G. Pagès, Distortion mismatch in the quantization of probability measures, ESAIM: Probability and Statistics, vol.12, pp.127-153, 2008.
DOI : 10.1051/ps:2007044

URL : https://hal.archives-ouvertes.fr/hal-00019228

P. Matilla, Geometry of Sets and Measures in Euclidean Spaces
DOI : 10.1017/CBO9780511623813

J. Mcnames, A fast nearest-neighbor algorithm based on a principal axis search tree, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.23, issue.9, pp.964-976, 2001.
DOI : 10.1109/34.955110

G. Pagès, A space quantization method for numerical integration, Journal of Computational and Applied Mathematics, vol.89, issue.1, pp.1-38, 1998.
DOI : 10.1016/S0377-0427(97)00190-8

G. Pagès, H. Pham, and J. Printems, AN OPTIMAL MARKOVIAN QUANTIZATION ALGORITHM FOR MULTI-DIMENSIONAL STOCHASTIC CONTROL PROBLEMS, Stochastics and Dynamics, vol.04, issue.04, pp.501-545, 2004.
DOI : 10.1142/S0219493704001231

G. Pagès, H. Pham, and J. Printems, Optimal quantization methods and applications to numerical problems in finance, Handbook on Numerical Methods in Finance, pp.253-298, 2004.

G. Pagès and J. Printems, Optimal quadratic quantization for numerics: the Gaussian case, Monte Carlo Methods and Applications, vol.9, issue.2, pp.135-165
DOI : 10.1515/156939603322663321