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

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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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Bibliographic Details
Other Authors: Wermter, Stefan (Editor) , Weber, Cornelius (Editor) , Duch, Włodzisław (Editor) , Honkela, Timo (Editor) , Koprinkova-Hristova, Petia (Editor) , Magg, Sven (Editor) , Palm, Günther (Editor) , Villa, Alessandro E. P. (Editor)
Format: Conference Paper
Language:English
Published: Cham [u.a.] Springer 2014
Series: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
Subjects:
Konferenzschrift
Künstliche Intelligenz
Maschinelles Lernen
Neuronales Netz
Online Access: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
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Author Notes:edited by Stefan Wermter, Cornelius Weber, Włodzisław Duch, Timo Honkela, Petia Koprinkova-Hristova, Sven Magg, Günther Palm, Alessandro E. P. Villa
Table of Contents:
  • Recurrent NetworksSequence Learning
  • Echo State Networks
  • Recurrent Network Theory
  • Competitive Learning and Self-Organisation.- Clustering and Classification
  • Trees and Graphs
  • Human-Machine Interaction
  • Deep Networks.- Theory
  • Optimization
  • Layered Networks
  • Reinforcement Learning and Action
  • Vision
  • Detection and Recognition
  • Invariances and Shape Recovery
  • Attention and Pose Estimation
  • Supervised Learning
  • Ensembles
  • Regression
  • Classification
  • Dynamical Models and Time Series
  • Neuroscience
  • Cortical Models
  • Line Attractors and Neural Fields
  • Spiking and Single Cell Models
  • Applications
  • Users and Social Technologies
  • Demonstrations.

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