Learning with recurrent neural networks :: SCD d'Orléans

Learning with recurrent neural networks

Learning with recurrent neural networks

Folding networks, a generalisation of recurrent neural networks to tree structured inputs, are investigated as a mechanism to learn regularities on classical symbolic data, for example. The architecture, the training mechanism, and several applications in different areas are explained. Afterwards a...

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Bibliografische gegevens
Hoofdauteur:	Hammer, Barbara
Formaat:	Livre numérique
Taal:	Anglais
Gepubliceerd in:	London ; Paris [etc.] : Springer-Verlag London Limited : Springer e-books [20..]. Cham : Springer Nature
Reeks:	Lecture notes in control and information sciences 254
Onderwerpen:	Réseaux neuronaux (informatique) Ingénierie
Online toegang:	Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL
Opmerking:	Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale)
Autres localisations:	Voir dans le Sudoc
Edition sous un autre format:	• Learning with recurrent neural networks, Barbara Hammer, London, Springer, 2000, X-148 p., Lecture notes in control and information sciences, 1-85233-343-X • Learning with Recurrent Neural Networks, Texte imprimé, 9781447139591

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