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When Noisy Labels Meet Long Tail Dilemmas: A Representation Calibration Method
In this paper, to handle the problem and address the limitations of prior works, we propose a representation calibration method RCAL.
Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration
In this paper, to address the distribution shift in learning with instance-dependent label noise, a dynamic distribution-calibration strategy is adopted.
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