Perfect learning in neural networks
: on sample complexity and scaling issues of gradient descent trained multilayer perceptrons and a novel object-oriented simulation framework for scalable information processing modules
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Titel:
Perfect learning in neural networks
:
on sample complexity and scaling issues of gradient descent trained multilayer perceptrons and a novel object-oriented simulation framework for scalable information processing modules