A stochastic backpropagation algorithm for training neural networks

The popularly used backpropagation algorithm (BP) for training multilayered neural networks is generally slow and prone to getting stuck in local minima. A novel method to improve the performance of the BP by randomising the cost function is proposed. The method is effective in helping the BP algori...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Chen, Y.Q., Yin, T., Babri, H.A.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Backpropagation algorithms Convergence Cost function Entropy Feedforward neural networks Jacobian matrices Multi-layer neural network Neural networks Pattern recognition Stochastic processes
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