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The computational intractability of training sigmoidal neural networks

✍ Scribed by Jones, L.K.


Book ID
114540592
Publisher
IEEE
Year
1997
Tongue
English
Weight
754 KB
Volume
43
Category
Article
ISSN
0018-9448

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In the present paper we develop two algorithms, subset-based training (SBT) and subset-based training and pruning (SBTP), using the fact that the Jacobian matrices in sigmoid network training problems are usually rank deficient. The weight vectors are divided into two parts during training, accordin