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Incorporating a priori Knowledge into Initialized Weights for Neural Classifier
Como, Italy July 24-July 27
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.857911IEEE-INNS-ENNS International Joint Co ...
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Zhe Chen, Ocean University of Qingdao
Tian-Jin Feng, Ocean University of Qingdao
Zweitze Houkes, Twente University
Artificial neural networks (ANN), esp. multilayer perceptrons (MLP) have been widely used in pattern recognition and classification. Nevertheless, how to incorporate a priori knowledge to design ANN is still an open problem. This paper tries to give some insightful discussions on this topic emphasizing weight initialization from three perspectives. Theoretical analyses and simulations are offered for validation.
Citation:
Zhe Chen, Tian-Jin Feng, Zweitze Houkes, "Incorporating a priori Knowledge into Initialized Weights for Neural Classifier," ijcnn, vol. 2, pp.2291, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2, 2000
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