For binary classification with noisy labels, the paper derives the Bayes-optimal function for combining a model's current predictions with the given labels during retraining, and shows a fitted version improves linear probing at high label noise.
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Self-Boost via Optimal Retraining: An Analysis via Approximate Message Passing
For binary classification with noisy labels, the paper derives the Bayes-optimal function for combining a model's current predictions with the given labels during retraining, and shows a fitted version improves linear probing at high label noise.