Neural network training algorithms on parallel architectures for finance applications

We focus on the neural network training problem that could be used for price forecasting or other purposes in finance. We design and develop four different parallel and multithreaded backpropagation neural network algorithms: neuron and training set parallelism on a distributed memory architecture u...

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Bibliographische Detailangaben

Hauptverfasser:	Thulasiram, R.K., Rahman, R.M., Thulasiraman, P.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Algorithm design and analysis Application software Backpropagation algorithms Economic forecasting Finance Memory architecture Neural networks Neurons Parallel architectures Parallel processing
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