Student loss: Towards the probability assumption in inaccurate supervision
Noisy labels are often encountered in datasets, but learning with them is challenging. Although natural discrepancies between clean and mislabeled samples in a noisy category exist, most techniques in this field still gather them indiscriminately, which leads to their performances being partially ro...
| Main Authors: | , , , , , |
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| Format: | Article |
| Published: |
IEEE Computer Society
2024
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| Subjects: |