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Comments on "Can backpropagation error surface not have local minima?"

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1 Author(s)
Hamey, L.G.C. ; Dept. of Comput., Macquarie Univ., North Ryde, NSW, Australia

in the above paper Yu (IEEE Trans. Neural Networks, vol.3, no.6, p.1019-21 (1992)) claims to prove that local minima do not exist in the error surface of backpropagation networks being trained on data with t distinct input patterns when the network is capable of exactly representing arbitrary mappings on t input patterns. The commenter points out that the proof presented is flawed, so that the resulting claims remain unproved. In reply, Yu points out that the undesired phenomenon that was sited can be avoided by simply imposing the arbitrary mapping capacity of the network on lemma 1 in the article.<>

Published in:

Neural Networks, IEEE Transactions on  (Volume:5 ,  Issue: 5 )

Date of Publication:

Sept. 1994

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