We consider the training of neural networks in cases where the nonlinear relationship of interest gradually changes over time. One possibility to deal with this problem is by regularization where a variation penalty is added to the usual mean squared error criterion. To learn the regularized network
An approximation theory approach to learning with regularization
β Scribed by Wang, Hong-Yan; Xiao, Quan-Wu; Zhou, Ding-Xuan
- Book ID
- 118257257
- Publisher
- Elsevier Science
- Year
- 2013
- Tongue
- English
- Weight
- 265 KB
- Volume
- 167
- Category
- Article
- ISSN
- 0021-9045
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