SIGUA: Forgetting May Make Learning with Noisy Labels More Robust

Given data with noisy labels, over-parameterized deep networks can gradually memorize the data, and fit everything in the end. Although equipped with corrections for noisy labels, many learning methods in this area still suffer overfitting due to undesired memorization... (read more)

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