Optimal Quantization : Evolutionary Algorithm vs Stochastic Gradient

DOI

10.2991/jcis.2006.161How to use a DOI?

Keywords

Evolutionary Optimization , Stochastic Gradient, Quantization

Abstract

We propose a new method based on evolutionary optimization for obtaining an optimal Lp-quantizer of a multidimensional random variable. First, we remind briefly the main results about quantization. Then, we present the classical gradient-based approach used up to now to find a “local” optimal Lp-quantizer. Then, we give an algorithm that permits to deal with the problem in the evolutionary optimization framework and illustrate a numerical comparison between the proposed method and the stochastic gradient method. Finally, a numerical application to option pricing in finance is provided.

Copyright

© 2006, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Moez MRAD
AU  - Sana BEN HAMIDA
PY  - 2006/10
DA  - 2006/10
TI  - Optimal Quantization : Evolutionary Algorithm vs Stochastic Gradient
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SP  - 652
EP  - 656
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.161
DO  - 10.2991/jcis.2006.161
ID  - MRAD2006/10
ER  -