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Maximizing Discrimination Capability of Knowledge Distillation with Energy Function
To distill optimal knowledge by adjusting non-target class predictions, we apply a higher temperature to low energy samples to create smoother distributions and a lower temperature to high energy samples to achieve sharper distributions.
Cosine Similarity Knowledge Distillation for Individual Class Information Transfer
Furthermore, we propose a method called cosine similarity weighted temperature (CSWT) to improve the performance.
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