Ternary Neural Networks with Fine-Grained Quantization
这篇文章主要针对以往三值量化一刀切的粗暴“量化”方式提出“细粒度”量化的想法。 文章目的将现有的网络不经训练地转化为三值网络，且激活函数8bit/4bit的。 相对于前人的工作，这篇文章的创新点在于Weight Grouping上。 3.1说应该将weights分为正交的子集。 3.2说3.1太麻烦了，直接按照顺序分成子集就好，真是纠结的一篇文章啊。 效果上，作者给出的字面数据是不错的。 结论
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相关文章
- 1. （笔记）细颗粒度的三值网络Ternary Neural Networks with Fine-Grained Quantization
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