Sparse neural network optimization by Simulated Annealing
The over-parameterization of neural networks and the local optimality of backpropagation algorithm have been two major problems associated with deep-learning. In order to reduce the redundancy of neural network parameters, the conventional approach has been to prune branches with small weights. Howe...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-09-01
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| Series: | Franklin Open |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2773186323000312 |