M. Abramovicz and I. A. Stegun, Handbook of Mathematical Functions, National Bureau of Standards, 1964.

V. Bally and G. Pagès, A quantization algorithm for solving multidimensional discrete-time optimal stopping problems, Bernoulli, vol.9, issue.6, pp.1003-1049, 2003.
DOI : 10.3150/bj/1072215199

URL : https://hal.archives-ouvertes.fr/hal-00104798

V. Bally and G. Pagès, Error analysis of the quantization algorithm for obstacle problems, Stochastic Process, Appl, vol.106, issue.1, pp.1-40, 2003.

V. Bally, G. Pagès, and J. Printems, A QUANTIZATION TREE METHOD FOR PRICING AND HEDGING MULTIDIMENSIONAL AMERICAN OPTIONS, Mathematical Finance, vol.26, issue.2, pp.119-168, 2005.
DOI : 10.1287/moor.27.1.121.341

URL : https://hal.archives-ouvertes.fr/hal-00101786

A. Benveniste, M. Métivier, and P. Priouret, Algorithmes adaptatifs and approximations stochastiques. Masson, Paris, 367 pp. English updated translation by Adaptive Algorithms and Stochastic Approximations, 1987.

N. Bouleau and D. Lépingle, Numerical methods for stochastic processes, Wiley Series in Probability and Mathematical Statistics: Applied Probability and Statistics, p.pp, 1994.

C. Bouton and G. Pagès, Self-organization and a.s. convergence of the one-dimensional Kohonen algorithm with non-uniformly distributed stimuli, Stochastic Processes and their Applications, vol.47, issue.2, pp.249-274, 1993.
DOI : 10.1016/0304-4149(93)90017-X

A. Brandejsky, B. De-saporta, and F. Dufour, Optimal stopping for partially observed piecewise-deterministic Markov processes, Stochastic Process, Appl, vol.123, issue.8, pp.3201-3238, 2013.
DOI : 10.1016/j.spa.2013.03.006

URL : http://arxiv.org/abs/1207.2886

A. Brandejsky, B. De-saporta, and F. Dufour, Numerical method for impulse control of piecewise deterministic Markov processes, Automatica, issue.5, pp.48779-793, 2012.

A. Brancolini, G. Butazzo, F. Santambrogio, and E. Stepanov, short-term planning in the asymptotical location problem, ESAIM: Control, Optimisation and Calculus of Variations, vol.15, issue.3, pp.509-524, 2009.
DOI : 10.1051/cocv:2008034

H. Cardot, P. Cénac, and J. Monnez, A fast and recursive algorithm for clustering large datasets with -medians, Computational Statistics & Data Analysis, vol.56, issue.6, pp.1431-1449, 2012.
DOI : 10.1016/j.csda.2011.11.019

URL : https://hal.archives-ouvertes.fr/hal-00644683

M. Corsi, H. Pham, and W. Runggaldier, Numerical approximation by quantization of control problems in finance under partial observation, chapter, Handbook of Numerical Analysis 15, pp.325-360, 2008.

M. Davis, Markov Models and Optimization, Monographs on Statistics & Applied Probability, 1993.

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

Q. Du, V. Faber, and M. Gunzburger, Centroidal Voronoi Tessellations: Applications and Algorithms, SIAM Review, vol.41, issue.4, pp.637-676, 1999.
DOI : 10.1137/S0036144599352836

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.407.146

J. 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

A. Gersho and R. M. Gray, Vector Quantization and Signal Compression, Springer International Series in Engineering and Computer Science, pp.159-732, 1991.
DOI : 10.1007/978-1-4615-3626-0

E. Gobet, G. Pagès, H. Pham, and J. Printems, Discretization and Simulation of the Zakai Equation, SIAM Journal on Numerical Analysis, vol.44, issue.6, pp.2505-2538, 2007.
DOI : 10.1137/050623140

URL : https://hal.archives-ouvertes.fr/hal-00394974

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

S. Graf, H. Luschgy, and G. Pagès, Optimal quantizers for Radon random vectors in a Banach space, Journal of Approximation Theory, vol.144, issue.1, pp.27-53, 2007.
DOI : 10.1016/j.jat.2006.04.006

URL : https://hal.archives-ouvertes.fr/hal-00004668

S. Graf, H. Luschgy, and G. Pagès, Distortion mismatch in the quantization of probability measures, ESAIM: Probability and Statistics, vol.12, pp.127-154, 2008.
DOI : 10.1051/ps:2007044

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

J. C. Kieffer, Exponential rate of convergence for Lloyd's method I, IEEE Transactions on Information Theory, vol.28, issue.2, pp.205-210, 1982.
DOI : 10.1109/TIT.1982.1056482

H. Luschgy, Martingale in diskreter Zeit, Theorie und Anwendungen Reihe, p.452, 2012.
DOI : 10.1007/978-3-642-29961-2

H. Luschgy and G. Pagès, Functional quantization rate and mean regularity of processes with an application to L??vy processes, The Annals of Applied Probability, vol.18, issue.2, pp.427-469, 2008.
DOI : 10.1214/07-AAP459

H. Niederreiter, Random Number Generation and Quasi-Monte Carlo Methods, CBMS-NSF regional conference series in Applied Mathematics, p.241, 1992.

G. Pagès, A space quantization method for numerical integration, Proceedings of the ESANN' 93, pp.1-38, 1993.
DOI : 10.1016/S0377-0427(97)00190-8

G. Pagès and H. Pham, Optimal quantization methods for nonlinear filtering with discrete-time observations, Bernoulli, vol.11, issue.5, pp.893-932, 2005.
DOI : 10.3150/bj/1130077599

G. Pagès, H. Pham, and J. Printems, Optimal quantization methods and applications to numerical problems in finance, Handbook on Numerical Methods in Finance, Birkhauser, pp.253-298, 2005.

G. Pagès, Introduction to Numerical Probability and Applications to Finance, to appear

G. Pagès and J. Printems, Functional quantization for numerics with an application to option pricing, Monte Carlo Methods and Applications, vol.11, issue.4, pp.407-446, 2005.
DOI : 10.1515/156939605777438578

G. Pagès and J. Printems, Optimal quantization for finance: from random vectors to stochastic processes, chapter from Mathematical Modeling and Numerical Methods in Finance, 2009.

Q. Bensoussan, Zhang guest eds.), coll. Handbook of Numerical Analysis, Ciarlet Editor), vol.15, pp.595-649

G. Pagès and Y. J. Xiao, Sequences with low discrepancy and pseudo-random numbers:theoretical results and numerical tests, Journal of Statistical Computation and Simulation, vol.185, issue.2, pp.163-183, 1997.
DOI : 10.1016/0022-314X(91)90055-G

H. Pham, W. Runggaldier, and A. Sellami, Approximation by quantization of the filter process and applications to optimal stopping problems under partial observation, Monte Carlo Methods and Applications, pp.57-81, 2004.

G. Pagès and J. Yu, Pointwise Convergence of the Lloyd I Algorithm in Higher Dimension, SIAM Journal on Control and Optimization, vol.54, issue.5, 2013.
DOI : 10.1137/151005622