Confidence Scores Make Instance-dependent Label-noise Learning Possible
Antonin Berthon 1 2 Bo Han 3 1 Gang Niu 1 Tongliang Liu 4 Masashi Sugiyama 1 5
Abstract orization effects (Zhang et al., 2017). Thus, learning with
noisy labels has often drawn a lot of attention.
In learning with noisy labels, for every instance,
its label can randomly walk to other classes fol- Early works on noisy labels studied random classif ...


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