Knowledge distillation (KD) is a machine learning technique similar to human educational wisdom, i.e., it uses a powerful teacher network to guide a weaker student network to learn knowledge. In this paper, the teacher and student networks in KD are abbreviated as teacher and student, respectively, for convenience.
Jan 16, 2024 · Inspired by human educational wisdom, this paper proposes a Student-Centered Distillation (SCD) method that enables the teacher network to ...
Article "Learning From Human Educational Wisdom: A Student-Centered Knowledge Distillation Method" Detailed information of the J-GLOBAL is an information ...
Co-authors ; Learning from human educational wisdom: A student-centered knowledge distillation method. S Yang, J Yang, MC Zhou, Z Huang, WS Zheng, X Yang, J Ren.
May 18, 2023 · We propose student-friendly knowledge distillation (SKD) to simplify teacher output into new knowledge representations, which makes the learning of the student ...
Oct 7, 2022 · Inspired by curriculum learning, we propose a novel knowledge distillation method via teacher-student cooperative curriculum customization.
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Knowledge distillation is a deep learning method that mimics the way that humans teach, i.e., a teacher network is used to guide the training of a student ...
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Interactive Knowledge Distillation is a general framework that is orthogonal to most existing knowledge distillation methods and trains the teacher model to ...
Jun 16, 2024 · This method focuses on minimizing the Kullback-Leibler (KL) divergence between the output distributions (logits) of the teacher and the student ...
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 ...