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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', paper presented at the Fifth Australian Conference on Neural Networks, February 1994, University of Queensland.
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Abstract
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) |
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Authors/Creators: | Vamplew, P and Adams, A |
Keywords: | recurrent neural networks, pre-training, weight initialisation |
Item Statistics: | View statistics for this item |
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