Systems and methods for contrastive learning with self-labeling refinement
Embodiments described herein provide a contrastive learning mechanism with self - labeling refinement , which iteratively employs the network and data themselves to generate more accurate and informative soft labels for contrastive learning . Specifically , the contrastive learning framework include...
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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/9806 https://ink.library.smu.edu.sg/context/sis_research/article/10806/viewcontent/2022_US_Patent_Contrastive_Learning.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | Embodiments described herein provide a contrastive learning mechanism with self - labeling refinement , which iteratively employs the network and data themselves to generate more accurate and informative soft labels for contrastive learning . Specifically , the contrastive learning framework includes a self - labeling refinery module to explicitly generate accurate labels , and a momentum mix - up module to increase similarity between a query and its positive , which in turn implicitly improves label accuracy. |
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