An empirical study on data distribution-aware test selection for deep learning enhancement
Similar to traditional software that is constantly under evolution, deep neural networks need to evolve upon the rapid growth of test data for continuous enhancement (e.g., adapting to distribution shift in a new environment for deployment). However, it is labor intensive to manually label all of th...
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| Main Authors: | , , , , , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2022
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/7195 https://ink.library.smu.edu.sg/context/sis_research/article/8198/viewcontent/3511598.pdf |
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| Institution: | Singapore Management University |
| Language: | English |