| Neural network learning without backpropagation. | |
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MedLine Citation:
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PMID: 20858577 Owner: NLM Status: In-Process |
Abstract/OtherAbstract:
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The method introduced in this paper allows for training arbitrarily connected neural networks, therefore, more powerful neural network architectures with connections across layers can be efficiently trained. The proposed method also simplifies neural network training, by using the forward-only computation instead of the traditionally used forward and backward computation. |
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Authors:
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Bogdan M Wilamowski; Hao Yu |
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Publication Detail:
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Type: Journal Article Date: 2010-09-20 |
Journal Detail:
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Title: IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council Volume: 21 ISSN: 1941-0093 ISO Abbreviation: IEEE Trans Neural Netw Publication Date: 2010 Nov |
Date Detail:
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Created Date: 2010-11-04 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101211035 Medline TA: IEEE Trans Neural Netw Country: United States |
Other Details:
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Languages: eng Pagination: 1793-803 Citation Subset: IM |
Affiliation:
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Department of Electrical and Computer Engineering, Auburn University, Auburn, AL 36849-5201 USA. wilam@ieee.org |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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