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Using Segmentation to Control the Retrieval of Data
University of Skövde, School of Humanities and Informatics.
University of Skövde, School of Humanities and Informatics.
2006 (English)In: 2006 International Joint Conference on Neural Networks (IJCNN2006),: Vancouver, BC, Canada, July 16-21 2006, IEEE Press, 2006, 1764-1769 p.Conference paper, (Other academic)
Abstract [en]

One problem when storing sequential data using recurrent neural networks is that it is hard to preserve long term dependencies. Only the most recently stored data tend to be accurately recalled. One approach for reducing this recency effect has been to divide the data into segments and store the segments separately. This approach has provided promising results in prediction and classification domains. This paper analyzes in what way recall of the stored data is affected by segmentation. It is concluded that segmentation enables the control of which data that can be recalled. The problem of preserving long term dependencies in recurrent neural networks can therefore be reduced.

Place, publisher, year, edition, pages
IEEE Press, 2006. 1764-1769 p.
Identifiers
URN: urn:nbn:se:his:diva-1922DOI: 10.1109/IJCNN.2006.246649ISI: 000245125903024Scopus ID: 2-s2.0-40649115252ISBN: 0-7803-9490-9 OAI: oai:DiVA.org:his-1922DiVA: diva2:32198
Available from: 2007-09-21 Created: 2007-09-21 Last updated: 2013-03-20

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Citation style
  • apa
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