[论文解读] DSD -- Dense-Sparse-Dense Training for Neural Network
《DSD: Dense-Sparse-Dense Training for Neural Network》发表在ICLR17， 这是一篇关注于提升模型训练得到的准确率的文章，而不是一作传统的研究领域：模型压缩。 DSD是一种新的训练模型的方式，可以提高预训练模型的准确率。DSD和dropout不一样，虽然都是在训练过程中有prune（剪枝）操作，但是DSD是有一定依据来选择去掉哪些connecti
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相关文章
- 1. Tips for Training Deep Neural Network
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- 3. 论文解读-Bag of Freebies for Training Object Detection Neural Networks
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