Knowledge distillation is a common method of model compression, which uses large models (teacher networks) to guide the training of small models (student ...
Knowledge distillation is a common method of model compression, which uses large models (teacher networks) to guide the training of small models (student ...
In this paper, we see knowledge distillation in a fresh light, using the knowledge gap between a teacher and a student as guidance to train a lighter-weight ...
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Oct 4, 2023 · Abstract:Knowledge distillation (KD) improves the performance of a low-complexity student model with the help of a more powerful teacher.
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While knowledge distillation can improve student generalization, it does not typically work as it is commonly understood: there often remains a surprisingly ...
Feb 11, 2024 · Knowledge distillation aims to transfer useful information from a teacher network to a student network, with the primary goal of improving the student's ...
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Nov 3, 2023 · Contrastive Learning methods encourage the student's representation of one sample to be similar or different to the teacher's representation of ...
Oct 7, 2022 · Inspired by curriculum learning, we propose a novel knowledge distillation method via teacher-student cooperative curriculum customization.
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Nov 28, 2023 · Knowledge distillation is a family of techniques with no clear goal. In the literature, it seems to me there are two types of knowledge distillation goals that ...
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Knowledge distillation is an effective way to transfer knowledge from a large model to a small model, which can significantly improve the performance of the ...