Friendly sharpness-aware minimization
Sharpness-Aware Minimization (SAM) has been instrumental in improving deep neural network training by minimizing both training loss and loss sharpness. Despite the practical success, the mechanisms behind SAM’s generalization enhancements remain elusive, limiting its progress in deep learning optimi...
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| Main Authors: | , , , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2024
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/9018 https://ink.library.smu.edu.sg/context/sis_research/article/10021/viewcontent/2024_CVPR_FSAM.pdf |
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| Institution: | Singapore Management University |
| Language: | English |