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Memorization in deep learning: A survey
Late stop**: Avoiding confidently learning from mislabeled examples
Sample selection is a prevalent method in learning with noisy labels, where small-loss data
are typically considered as correctly labeled data. However, this method may not effectively …
are typically considered as correctly labeled data. However, this method may not effectively …
Triage: Characterizing and auditing training data for improved regression
Data quality is crucial for robust machine learning algorithms, with the recent interest in data-
centric AI emphasizing the importance of training data characterization. However, current …
centric AI emphasizing the importance of training data characterization. However, current …