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Inference-Time Prior Adaptation for Imbalanced Data Streams under Concept Drift
Data stream classification under concept drift and class imbalance requires models to adapt continuously while maintaining strong minority-class performance. Many existing approaches rely on active memory management, in- cluding instance removal, memory restructuring, resampling, and synthetic data
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