Artificial Neural Networks and Machine Learning -- ICANN 2014
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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
Palm, Guenther; Wermter, Stefan; Magg, Sven; Weber, Cornelius; Honkela, Timo; Koprinkova-Hristova, Petia; Villa, Allessandro E.P.; Duch, Wlodzislaw
Springer International Publishing AG
09/2014
852
Mole
Inglês
9783319111780
15 a 20 dias
Descrição não disponível.
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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
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
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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
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
