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The GK-KD framework we propose enhances network performance by distilling accurate and important knowledge.
The GK-KD framework we propose enhances network performance by distilling accurate and important knowledge. •. Experiments show our framework balances ...
Apr 12, 2024 · The GK-KD framework we propose enhances network performance by distilling accurate and important knowledge. •. Experiments show our framework ...
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Download Citation | On Feb 1, 2024, Junhuang Wang and others published Global key knowledge distillation framework | Find, read and cite all the research ...
Feb 1, 2024 · Global key knowledge distillation framework. Machine Learning · Computer Science · Mathematics. Show More. Authors. Junhuang Wang,Weiwei Zhang.
Amik; Bhandare; Chen, J., Chen, S., Pan, S.J., 2020a. Storage efficient and dynamic flexible runtime channel pruning via deep reinforcement learning.
Jul 10, 2023 · To overcome these challenges, we present a gen- eral knowledge distillation framework (GKD) for deploying knowledge distillation systems that ...
Oct 22, 2024 · A novel framework that leverages knowledge distillation from Cox Proportional Hazards (CoxPH) models to create synthetic survival datasets.
Feb 24, 2024 · Basically, a knowledge distillation system is composed of three key components: knowledge, distillation algorithm, and teacher-student ...
Knowledge Distillation is model compression method in which a small model is trained to mimic a pre-trained, larger model (or ensemble of models).