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Robust Long-Tailed Learning: Overcoming Label Noise via Small-Distance Criterion
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Robust Long-Tailed Learning: Overcoming Label Noise via Small-Distance Criterion
Addressing the realistic yet challenging scenario of long-tailed distributions paired with label noise, a joint team from Southeast and Nanjing University identified that the common "small-loss" criterion fails for tail classes.
·Charlottesville, United States
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