WebDec 19, 2014 · FitNets: Hints for Thin Deep Nets Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang, Carlo Gatta, Yoshua Bengio While depth tends to … WebPytorch implementation of various Knowledge Distillation (KD) methods. - Knowledge-Distillation-Zoo/fitnet.py at master · AberHu/Knowledge-Distillation-Zoo

【知识蒸馏】FitNets：Hints for thin deep nets - 知乎

Web随着科学研究与生产实践相结合需求的与日俱增，模型压缩和加速成为当前的热门研究方向之一。本文旨在对一些常见的模型压缩和模型加速方法进行简单介绍（每小节末尾都整理了一些相关工作，感兴趣的小伙伴欢迎查阅）。这些方法可以减少模型中存在的冗余，将复杂模型转化成更轻量的模型。 WebWe propose a novel approach to train thin and deep networks, called FitNets, to compress wide and shallower (but still deep) networks. The method is rooted in the recently … green construction advisory panel

Knowledge-Distillation-Zoo/fitnet.py at master - Github

Web这是知识蒸馏的第二篇文章，文章认为 Hinton 提出的 knowledge distillation 方法 (KD) 简单的拟合 Teacher 模型的输出并不能使 Student 达到和 Teacher 一样的泛化性能。对此， … WebDec 19, 2014 · In this paper, we extend this idea to allow the training of a student that is deeper and thinner than the teacher, using not only the outputs but also the intermediate representations learned by the teacher as hints to improve the training process and final performance of the student. WebDec 19, 2014 · FitNets: Hints for Thin Deep Nets. While depth tends to improve network performances, it also makes gradient-based training more difficult since deeper networks tend to be more non-linear. flow the team snowboard review