Learning with Recurrent Neural Networks (eBook, PDF)
Barbara Hammer
eBook, PDF

Learning with Recurrent Neural Networks (eBook, PDF)

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Folding networks, a generalisation of recurrent neural networks to tree structured inputs, are investigated as a mechanism to learn regularities on classical symbolic data, for example. The architecture, the training mechanism, and several applications in different areas are explained. Afterwards a theoretical foundation, proving that the approach is appropriate as a learning mechanism in principle, is presented: Their universal approximation ability is investigated- including several new results for standard recurrent neural networks such as explicit bounds on the required number of neurons a...

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