Compression of Deep-Learning Models Through Global Weight Pruning Using Alternating Direction Method of Multipliers
Abstract Deep learning has shown excellent performance in numerous machine-learning tasks, but one practical obstacle in deep learning is that the amount of computation and required memory is huge. Model compression, especially in deep learning, is very useful because it saves memory and reduces sto...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2023-02-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44196-023-00202-z |