Foundations of computational intelligence. Volume 1, Learning and approximation
Learning methods and approximation algorithms are fundamental tools that deal with computationally hard problems and problems in which the input is gradually disclosed over time. Both kinds of problems have a large number of applications arising from a variety of fields, such as algorithmic game the...
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| Autres auteurs: | , , , , |
|---|---|
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Édition: | 1st ed. 2009. |
| Collection: | Studies in Computational Intelligence
201 |
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Foundations of computational intelligence, Volume 1, Learning and approximation, Aboul-Ella Hassanien, Ajith Abraham, Athanasios V. Vasilakos and Witold Pedrycz (eds), Berlin Heidelberg, Springer, 2009, 1 vol. (XII-397 p.), Studies in computational intelligence, 978-3-642-01081-1 • Foundations of Computational Intelligence, Texte imprimé, 9783642010835 • Foundations of computational intelligence, Volume 1, Learning and approximation, Aboul-Ella Hassanien, Ajith Abraham, Athanasios V. Vasilakos and Witold Pedrycz (eds), Berlin Heidelberg, Springer, 2009, 1 vol. (XII-397 p.), Studies in computational intelligence, 978-3-642-01081-1 • Foundations of Computational Intelligence, Texte imprimé, 9783662568439 |