Artificial Neural Networks and Machine Learning – ICANN 2014: 24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15 - 19, 2014. Proceedings

The book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on follow...

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Weitere Verfasser: Wermter, Stefan (HerausgeberIn) , Weber, Cornelius (HerausgeberIn) , Duch, Włodzisław (HerausgeberIn) , Honkela, Timo (HerausgeberIn) , Koprinkova-Hristova, Petia (HerausgeberIn) , Magg, Sven (HerausgeberIn) , Palm, Günther (HerausgeberIn) , Villa, Alessandro E. P. (HerausgeberIn)
Dokumenttyp: Konferenzschrift
Sprache:Englisch
Veröffentlicht: Cham [u.a.] Springer 2014
Schriftenreihe:Lecture notes in computer science 8681
In: Lecture notes in computer science (8681)

Volumes / Articles: Show Volumes / Articles.
DOI:10.1007/978-3-319-11179-7
Schlagworte:
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1007/978-3-319-11179-7
Resolving-System, lizenzpflichtig, Volltext: http://dx.doi.org/10.1007/978-3-319-11179-7
Cover: https://swbplus.bsz-bw.de/bsz414026888cov.jpg
Volltext
Verfasserangaben:edited by Stefan Wermter, Cornelius Weber, Włodzisław Duch, Timo Honkela, Petia Koprinkova-Hristova, Sven Magg, Günther Palm, Alessandro E. P. Villa
Beschreibung
Zusammenfassung:The book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on following topics: recurrent networks; competitive learning and self-organisation; clustering and classification; trees and graphs; human-machine interaction; deep networks; theory; reinforcement learning and action; vision; supervised learning; dynamical models and time series; neuroscience; and applications
Beschreibung:Literaturangaben
Beschreibung:Online Resource
ISBN:9783319111797
DOI:10.1007/978-3-319-11179-7