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Abstract: Imbalanced data classification remains a fundamental challenge in machine learning, especially in multi-class scenarios where feature noise, class overlap, and small disjunct sub-concepts ...
Abstract: Neural collapse describes the optimal learned representation features and their corresponding optimal classifier that globally minimizes the training loss in deep classifier neural networks.