Optimal Quantization : Evolutionary Algorithm vs Stochastic Gradient
Moez MRAD 0, Sana BEN HAMIDA
0Societe Generale and CERMSEM, Universite Paris I , France
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- https://doi.org/10.2991/jcis.2006.161How to use a DOI?
- Evolutionary Optimization , Stochastic Gradient, Quantization
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Moez MRAD AU - Sana BEN HAMIDA PY - NaN/NaN DA - NaN/NaN TI - Optimal Quantization : Evolutionary Algorithm vs Stochastic Gradient BT - 9th Joint International Conference on Information Sciences (JCIS-06) PB - Atlantis Press UR - https://doi.org/10.2991/jcis.2006.161 DO - https://doi.org/10.2991/jcis.2006.161 ID - MRADNaN/NaN ER -