Artificial Neural Networks and Machine Learning -- ICANN 2014

24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014, Proceedings

Stefan Wermter, Cornelius Weber, Wlodzislaw Duch, Timo Honkela, Petia Koprinkova-Hristova, Sven Magg, Günther Palm, Allessandro E.P. Villa (Herausgeber)

Buch | Softcover

XXV, 852 Seiten

2014
Springer International Publishing (Verlag)
978-3-319-11178-0 (ISBN)

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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 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.

Recurrent Networks.- Sequence 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.

Erscheint lt. Verlag	22.9.2014
Reihe/Serie	Lecture Notes in Computer Science
Reihe/Serie	Theoretical Computer Science and General Issues
Zusatzinfo	XXV, 852 p. 338 illus.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	1300 g
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
Schlagworte	Algorithm analysis and problem complexity • Computational Neuroscience • distributed computation • Dynamical Systems • Ensemble methods • evolving systems • machine learning • Neural networks • parallel distributed system • Particle swarm optimization • Reinforcement Learning • robust pattern recognition • Self-Organizing Maps • Speech Recognition • Support Vector Machines • Swarm intelligence • Turing Machines • Unsupervised Learning
ISBN-10	3-319-11178-7 / 3319111787
ISBN-13	978-3-319-11178-0 / 9783319111780
Zustand	Neuware