Building efficient and practical machine learning systems
With the widespread adoption of deep learning (DL) applications in recent years, training DL models has become increasingly prevalent. Nevertheless, training these models is typically time-consuming and computation-intensive, relying heavily on expensive heterogeneous infrastructure. To facilitate m...
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格式: | Thesis-Doctor of Philosophy |
語言: | English |
出版: |
Nanyang Technological University
2023
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在線閱讀: | https://hdl.handle.net/10356/172372 |
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