Approximate computing for machine learning
Approximate Computing has emerged as a promising paradigm to enhance computational efficiency by introducing controlled inaccuracies in arithmetic operations. This study explores the application of static approximate adders (AAs) within a machine learning context, specifically the K-means clus...
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格式: | Final Year Project |
語言: | English |
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Nanyang Technological University
2025
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在線閱讀: | https://hdl.handle.net/10356/183990 |
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機構: | Nanyang Technological University |
語言: | English |