Artificial Neural Networks and Machine Learning -- ICANN 2014: 24th International Conference on Artificial Neural Networks, Hamburg, Germany, September 15-19, 2014, Proceedings: Lecture Notes in Computer Science, cartea 8681
Editat de Stefan Wermter, Cornelius Weber, Wlodzislaw Duch, Timo Honkela, Petia Koprinkova-Hristova, Sven Magg, Günther Palm, Allessandro E.P. Villaen Limba Engleză Paperback – 22 sep 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.
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Specificații
ISBN-13: 9783319111780
ISBN-10: 3319111787
Pagini: 880
Ilustrații: XXV, 852 p. 338 illus.
Dimensiuni: 155 x 235 x 46 mm
Greutate: 1.21 kg
Ediția:2014
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Theoretical Computer Science and General Issues
Locul publicării:Cham, Switzerland
ISBN-10: 3319111787
Pagini: 880
Ilustrații: XXV, 852 p. 338 illus.
Dimensiuni: 155 x 235 x 46 mm
Greutate: 1.21 kg
Ediția:2014
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Theoretical Computer Science and General Issues
Locul publicării:Cham, Switzerland
Public țintă
ResearchCuprins
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.