Artificial Neural Networks and Machine Learning -- ICANN 2014, 2014 24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014, Proceedings Theoretical Computer Science and General Issues Series
Coordonnateurs : Wermter Stefan, Weber Cornelius, Duch Wlodzislaw, Honkela Timo, Koprinkova-Hristova Petia, Magg Sven, Palm Günther, Villa Allessandro E.P.
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.
Date de parution : 09-2014
Ouvrage de 852 p.
15.5x23.5 cm
Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).
Prix indicatif 52,74 €
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Mots-clés :
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; algorithm analysis and problem complexity