Tailored Channel Pruning: Achieve Targeted Model Complexity Through Adaptive Sparsity Regularization
In deep learning, the size and complexity of neural networks have been rapidly increased to achieve higher performance. However, this poses a challenge when utilized in resource-limited environments, such as mobile devices, particularly when trying to preserve the network’s performance. T...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10840184/ |
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