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Bounded Adjustment with Reliability-Guided Embedding for Imbalanced Learning with Noisy Labels
Class-balanced learning and label noise create a coupled failure mode: frequency correction prevents majority classes from dominating the decision rule, but can amplify incorrectly labeled minority examples. We introduce BARGE (Bounded Adjustment with Reliability-Guided Embeddings), a single-stage o
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