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Improving Knowledge Distillation via Transferring Learning Ability

Published 24 Apr 2023 in cs.CV | (2304.11923v2)

Abstract: Existing knowledge distillation methods generally use a teacher-student approach, where the student network solely learns from a well-trained teacher. However, this approach overlooks the inherent differences in learning abilities between the teacher and student networks, thus causing the capacity-gap problem. To address this limitation, we propose a novel method called SLKD.

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