Research map / Label-efficient and robust learning / Noisy labels
Error-Bounded Correction of Noisy Labels
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use a noisy classifier with approximation error ε in LRT-Correction | LRT-Correction · Noisy-label classification under the multi-class Tsybakov condition | probability of incorrect corrected labels | Hurt |
| Use an approximate rather than exact critical value, with error ξ | LRT-Correction · Noisy-label classification under the multi-class Tsybakov condition | probability of incorrect corrected labels | Hurt |
| Apply LRT-Correction using the exact noisy-label classifier | LRT-Correction · Synthetic mixture-of-Gaussians with symmetric or asymmetric noise | corrected-label quality | Helped |
Closest papers by meaning
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- Handling Label Noise via Instance-Level Difficulty Modeling and Dynamic Optimization (NeurIPS 2025 · similarity 0.89)
- Revisiting Interpolation for Noisy Label Correction (AAAI 2025 · similarity 0.87)
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