
Be the first to like this
Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our User Agreement and Privacy Policy.
Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our Privacy Policy and User Agreement for details.
Published on
@inproceedings{teytaud:inria00451416,
hal_id = {inria00451416},
url = {http://hal.inria.fr/inria00451416},
title = {{Bias and variance in continuous EDA}},
author = {Teytaud, Fabien and Teytaud, Olivier},
abstract = {{Estimation of Distribution Algorithms are based on statistical estimates. We show that when combining classical tools from statistics, namely bias/variance decomposition, reweighting and quasirandomization, we can strongly improve the convergence rate. All modifications are easy, compliant with most algorithms, and experimentally very efficient in particular in the parallel case (large offsprings).}},
language = {Anglais},
affiliation = {TAO  INRIA Futurs , Laboratoire de Recherche en Informatique  LRI , TAO  INRIA Saclay  Ile de France},
booktitle = {{EA 09}},
address = {Strasbourg, France},
audience = {internationale },
year = {2009},
month = May,
pdf = {http://hal.inria.fr/inria00451416/PDF/decsigma.pdf},
}
Be the first to like this
Clipping is a handy way to collect and organize the most important slides from a presentation. You can keep your great finds in clipboards organized around topics.
Be the first to comment