Sharp asymptotics of the functional quantization problem for Gaussian processes

By Harald Luschgy, Gilles Pagès. 2004

94 citations recorded by the source corpus.

The sharp asymptotics for the 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.

Subfields: Applied Mathematics, Computer Vision and Pattern Recognition, Finance

View Paper: https://www.semanticscholar.org/paper/607a8cb3e19bbe857394db146f83c62ca5528fa0

How researchers see this paper

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In Applied Mathematics

1. Harald Luschgy
2. Gilles Pagès

In Computer Vision and Pattern Recognition

1. Gilles Pagès
2. S. Yu. Graf
3. Harald Luschgy

In Finance

1. Gilles Pagès
2. Harald Luschgy
3. Huyen Pham

Citations in the corpus

• Functional quantization rate and mean regularity of processes with an application to Lévy processes (2006, background): “For more details on the existence problem for optimal quantizers, we refer to [15].”
• MULTIFRACTIONAL STOCHASTIC VOLATILITY MODELS (2011, unknown): “More precise results were then established in [51].”
• DISTORTION MISMATCH IN THE QUANTIZATION OF PROBABILITY MEASURES (2006, background): “All these quantities do have explicit expressions (see [9, 12] among others).”
• On the mean speed of convergence of empirical and occupation measures in Wasserstein distance (2011, unknown): “We introduce the measure mj ∧ nj + m̃j−1 defined by [mj ∧ nj + m̃j−1](xj,l) = mj ∧ nj (xj,l), [mj ∧ nj + m̃j−1](xj−1,l′) = m̃j−1(xj−1,l′).”