The Hessian by blocks for neural network by backward propagation
The back-propagation algorithm used with a stochastic gradient and the increase in computer performance are at the origin of the recent Deep learning trend. For some problems, however, the convergence of gradient methods is still very slow. Newton's method offers potential advantages in terms o...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
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| Series: | Journal of Taibah University for Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/16583655.2024.2327102 |
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