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Neural Transplant Surgery: An Approach to Pre-training Recurrent Networks


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Vamplew, P and Adams, A (1994) Neural Transplant Surgery: An Approach to Pre-training Recurrent Networks. In: Fifth Australian Conference on Neural Networks, February 1994, University of Queensland.

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Partially-recurrent networks have advantages over strictly feed-forward networks for certain spatiotemporal pattern classification or prediction tasks. However networks involving recurrent links are generally more difficult to train than their non-recurrent counterparts. In this paper we demonstrate that the costs of training a recurrent network can be greatly reduced by initialising the network prior to training with weights 'transplanted' from a non-recurrent architecture.

Item Type: Conference or Workshop Item (Paper)
Authors/Creators:Vamplew, P and Adams, A
Keywords: recurrent neural networks, pre-training, weight initialisation
Date Deposited: 12 Aug 2004
Last Modified: 18 Nov 2014 03:10
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