@article {54,
	title = {Entropy-constrained functional quantization of Gaussian measures},
	journal = {Proceedings AMS},
	volume = {133},
	year = {2005},
	pages = {3403-3409 },
	abstract = {The sharp asymptotics for the entropy-constrained $L^2$-quantization errors of Gaussian measures on a Hilbert space and in particular, for Gaussian processes is derived. The condition imposed is regular variation of the eigenvalues of the covariance operator.
},
	author = {Harald Luschgy and Siegfried Graf}
}
@article {31,
	title = {Error analysis of the quantization algorithm for obstacle problems},
	journal = {Stochastic Processes \& Their Applications},
	volume = {106(1)},
	year = {2003},
	chapter = {1-40},
	abstract = {In the accompanying paper [2] an algorithm based on a "quantized tree" is designed to compute the solution of multi-dimensional obstacle problems for homogeneous $\mathbb{R}^d$-valued Markov chains. It is based on the quantization of probability distributions which yields a dynamic programming formula on a discrete tree. A typical example of such problems is the pricing of multi-asset American style vanilla options. In the first part of the present paper, the analysis of the $L^p$-error is completed. In the second part, we estimate the error induced by the Monte Carlo estimation of the transition weights involved in the (optimal) quantized tree.},
	keywords = {American option pricing, Numerical Probability, Optimal Stopping, Quantization of random variables, Reflected Backward Stochastic Differential Equation, Snell envelope},
	author = {Vlad Bally and Gilles Pag{\`e}s}
}
